Operatorless particle processing systems and methods

ABSTRACT

The present disclosure provides improved particle processing (e.g., cytometry and/or cell purification) systems and methods that can operate in an autonomous fashion. More particularly, the present disclosure provides for assemblies, systems and methods for analyzing, sorting, and/or processing (e.g., purifying, measuring, isolating, detecting and/or enriching) particles (e.g., cells, microscopic particles, etc.) where human intervention is not required and/or is minimized. The systems, assemblies and methods of the present disclosure advantageously improve run performance of particle processing systems (e.g., cell purification systems, cytometers) by significantly reducing and/or substantially eliminating the burden of operation for human intervention by automating numerous functions, features and/or steps of the disclosed systems and methods.

RELATED APPLICATION

This application is a continuation of U.S. patent application Ser. No.14/210,381, filed Mar. 13, 2014, now U.S. Pat. No. 9,964,968, whichclaims the benefit of priority to U.S. Provisional Application Ser. No.61/784,170, titled “Operatorless Particle Processing Systems andMethods,” and filed Mar. 14, 2013, the content of each of the aboveapplications being hereby incorporated by reference in its entirety.

TECHNICAL FIELD

The present disclosure relates to particle processing systems andmethods that can operate in an operatorless fashion and, moreparticularly, to assemblies, systems, methods and steps associated withprocessing particles where human intervention is not required and/or isminimized.

BACKGROUND

In general, particle processing (e.g., cytometry) systems (e.g.,cytometers) and methods are known. For example, some approaches toparticle processing or analyzing (e.g., cell purification) systems suchas sorting flow cytometers and other particle processing systems haveproven to be useful in life science research, industrial, agricultural,diagnostics, and other medical applications.

In general, a cytometer can be described as a system that can measurelarge numbers of homogeneous and/or heterogeneous particle sets toachieve statistically relevant data sets that can be used to groupand/or identify subpopulations that reside within a given particlepopulation (e.g., within one or more samples). These measurements aresometimes performed optically (whether they are intrinsic or responsiveto an optical stimulus), or they may be electrical in nature (or someother physical, chemical, or biological characteristic) as a stream ofparticles passes through a measurement or inspection zone. The particlesets may include biological entities such as cells (e.g., bacteria,viruses, organelles, yeasts, spores, genetic material, spermatozoa, eggcells, multicellular organisms), or other organisms, or other naturallyoccurring or synthetic/synthetically derived objects.

With the addition of sort functionality, a cytometer can also be used toisolate (e.g., physically separate) one or more particles of interestfrom a given/presented sample through human/operator control. See, e.g.,U.S. Pat. No. 6,248,590, the entire content of which is herebyincorporated by reference in its entirety. In general, this techniquecan be used to classify and/or separate (e.g., purify or enrich) one ormore populations as defined by the operator.

SUMMARY

The present disclosure relates to particle processing systems, methods,and steps that can operate in an autonomous fashion and, moreparticularly, to assemblies, systems, methods, and steps for analyzing,sorting, and/or processing particles where human intervention is notrequired. The present disclosure also relates to particle processingsystems and methods that can operate in a semi-autonomous fashion and,more particularly, to assemblies, systems and methods for analyzing,sorting, and/or processing particles where human intervention isminimized.

The present disclosure provides advantageous particle processing oranalyzing systems and methods that can operate autonomously (i.e.,without operator intervention and/or having remote-controlled features).In general, the systems, assemblies and methods of the presentdisclosure advantageously improve run performance of particle processingsystems (e.g., cell purification systems, cytometers) by providingsystems and methods that significantly automate numerous functions,features and/or steps of the disclosed systems and methods. In exemplaryembodiments, the present disclosure provides for improved assemblies,systems, methods, and process steps associated with setting up,calibrating, aligning, analyzing, sorting, and/or processing (e.g.,purifying, measuring, isolating, detecting, monitoring and/or enriching)particles (e.g., cells, microscopic particles, etc.) where humanintervention is not required and/or is minimized.

The present disclosure provides for a particle processing systemincluding a detection region; a particle processing region; one or moresensors sensing one or more operational characteristics of the particleprocessing system; and a processor programmed and/or configured toautomatically change one or more parameters of the particle processingsystem based on the one or more operational characteristics sensed bythe one or more sensors.

The present disclosure also provides for a particle processing systemincluding a particle delivery assembly; a signal source assembly; aparticle analysis region assembly; a particle collection assembly; asignal detector assembly; at least one sensor assembly adapted to senseor monitor at least one processing feature of the particle deliveryassembly, signal source assembly, particle analysis region assembly,particle collection assembly or signal detector assembly; at least oneprocessor in communication with the at least one sensor assembly and theparticle delivery assembly, signal source assembly, particle analysisregion assembly, particle collection assembly or signal detectorassembly; wherein the at least one processor and the at least one sensorassembly, and the particle delivery assembly, signal source assembly,particle analysis region assembly, particle collection assembly orsignal detector assembly are configured and adapted to process particlesin an operatorless fashion.

The present disclosure also provides for a particle processing systemincluding a particle delivery assembly in communication with a firstsensing member, the first sensing member adapted to sense or monitor atleast one processing feature of the particle delivery assembly; a signalsource assembly in communication with a second sensing member, thesecond sensing member adapted to sense or monitor at least oneprocessing feature of the signal source assembly; a particle analysisregion assembly in communication with a third sensing member, the thirdsensing member adapted to sense or monitor at least one processingfeature of the particle analysis region assembly; a particle collectionassembly in communication with a fourth sensing member, the fourthsensing member adapted to sense or monitor at least one processingfeature of the particle collection assembly; a signal detector assemblyin communication with a fifth sensing member, the fifth sensing memberadapted to sense or monitor at least one processing feature of thesignal detector assembly; at least one processor in communication with:(i) the first sensor assembly, second sensor assembly, third sensorassembly, fourth sensor assembly and fifth sensor assembly, and (ii) theparticle delivery assembly, signal source assembly, particle analysisregion assembly, particle collection assembly and signal detectorassembly; wherein the at least one processor and the first sensorassembly, second sensor assembly, third sensor assembly, fourth sensorassembly, fifth sensor assembly, particle delivery assembly, signalsource assembly, particle analysis region assembly, particle collectionassembly and signal detector assembly are configured and adapted toprocess particles in an operatorless fashion.

The present disclosure also provides for a particle processing systemincluding a particle delivery assembly, the particle delivery assemblyconfigured to deliver a stream containing particles to an inspectionregion; an electromagnetic radiation source assembly; a particlecollection assembly; a signal detector assembly; at least one sensorassembly adapted to sense or monitor at least one processing feature ofthe particle delivery assembly, electromagnetic radiation sourceassembly, particle inspection region, particle collection assembly orsignal detector assembly; at least one processor in communication withthe at least one sensor assembly and the particle delivery assembly,electromagnetic radiation source assembly, particle inspection region,particle collection assembly or signal detector assembly; wherein the atleast one processor and the at least one sensor assembly, and theparticle delivery assembly, electromagnetic radiation source assembly,particle inspection region, particle collection assembly or signaldetector assembly are configured and adapted to process particles in anoperatorless fashion.

The present disclosure also provides for a particle processing systemincluding a particle delivery assembly; an electromagnetic radiationsource assembly; a microfluidic assembly, the microfluidic assemblyincluding a particle inspection region; a particle collection assembly;an optical detector assembly; at least one sensor assembly adapted tosense or monitor at least one processing feature of the particledelivery assembly, electromagnetic radiation source assembly,microfluidic assembly, particle collection assembly or optical detectorassembly; at least one processor in communication with the at least onesensor assembly and the particle delivery assembly, electromagneticradiation source assembly, microfluidic assembly, particle collectionassembly or optical detector assembly; wherein the at least oneprocessor and the at least one sensor assembly, and the particledelivery assembly, electromagnetic radiation source assembly,microfluidic assembly, particle collection assembly or optical detectorassembly are configured and adapted to process particles in anoperatorless fashion.

The present disclosure also provides for a particle processing systemincluding a plurality of particle processing assemblies, each particleprocessing assembly including: a detection region; a particle processingregion; one or more sensors, the one or more sensors sensing one or moreoperational characteristics of the associated particle processingassembly; and a processor programmed and/or configured to automaticallychange one or more parameters of its associated particle processingassembly based on the one or more operational characteristics sensed bythe one or more sensors.

The present disclosure also provides for a particle processing systemincluding a detection region; a particle processing region; one or moresensors sensing one or more operational characteristics of the particleprocessing system; and a remote processor, the remote processorprogrammed and/or configured to remotely control or change one or moreparameters of the particle processing system based on the one or moreoperational characteristics sensed by the one or more sensors.

Any combination or permutation of embodiments is envisioned. Additionaladvantageous features, functions and applications of the disclosedsystems, assemblies and methods of the present disclosure will beapparent from the description which follows, particularly when read inconjunction with the appended figures.

BRIEF DESCRIPTION OF THE DRAWINGS

Exemplary embodiments of the present disclosure are further describedwith reference to the appended figures. It is to be noted that thevarious features and combinations of features described below andillustrated in the figures can be arranged and/organized differently toresult in embodiments which are still within the spirit and scope of thepresent disclosure. To assist those of ordinary skill in the art inmaking and using the disclosed systems, assemblies and methods,reference is made to the appended figures.

FIG. 1 is a block diagram of an exemplary embodiment of a particleprocessing system according to the present disclosure.

FIG. 2 is a block diagram of another exemplary embodiment of a particleprocessing system according to the present disclosure.

FIG. 3 illustrates an exemplary particle processing system of FIG. 2.

FIGS. 4A and 4B illustrate screen shots of an exemplary embodiment of anaspect of a particle processing system according to the presentdisclosure.

FIG. 5 depicts a screenshot from an exemplary fluidic stability monitorof the system of FIG. 3.

FIG. 6 is a block diagram of another exemplary embodiment of a particleprocessing system according to the present disclosure.

FIG. 7 illustrates an exemplary particle processing system of FIG. 6.

FIG. 8 illustrates an exemplary microfluidic assembly of the presentdisclosure.

FIG. 9 illustrates a cross-section through channels of an exemplarymicrofluidic assembly of the present disclosure.

FIG. 10 illustrates another exemplary microfluidic assembly of thepresent disclosure.

FIGS. 11A and 11B illustrate an exemplary coarse scanning process in ay-direction and collected data, respectively, for an exemplaryprocess/method for aligning a microfluidic assembly of the presentdisclosure.

FIGS. 12A and 12B illustrate an exemplary coarse scanning process in anx-direction and collected data, respectively, for the exemplaryprocess/method for aligning the microfluidic assembly of the presentdisclosure.

FIGS. 13A and 13B illustrate an exemplary three-dimensional graph and atwo dimensional graph, respectively, of data generated by coarsescanning to determine a coarse slant angle.

FIGS. 14A and 14B illustrate an exemplary fine scanning process in thex-direction and collected data, respectively, for the exemplaryprocess/method for aligning the microfluidic assembly of the presentdisclosure.

FIGS. 15A and 15B illustrate an exemplary fine scanning process in they-direction and collected data, respectively, for the exemplaryprocess/method for aligning the microfluidic assembly of the presentdisclosure.

FIGS. 16A and 16B illustrate an exemplary microfluidic chip at its finalaligned position and collected data, respectively.

FIGS. 17A and 17B illustrate an exemplary coarse scanning process in ay-direction and collected data, respectively, for another exemplaryprocess/method for aligning a microfluidic assembly of the presentdisclosure.

FIGS. 18A and 18B illustrate an exemplary coarse scanning process in anx-direction and collected data, respectively, for another exemplaryprocess/method for aligning the microfluidic assembly of the presentdisclosure.

FIGS. 19A and 19B illustrate an exemplary microfluidic chip that hasbeen deslanted by the negative of a slant angle determined during thecoarse scanning steps and collected data, respectively.

FIG. 20 illustrates optical transmissions of pinholes as a function ofscan increment.

FIGS. 21A and 21B illustrate an exemplary fine scanning process in thex-direction and collected data, respectively, for the second exemplaryprocess/method for aligning the microfluidic assembly of the presentdisclosure.

FIGS. 22A and 22B graphically illustrate exemplary optical power datafor pinholes of the second and fourth microfluidic channels,respectively.

FIGS. 23A and 23B illustrate an exemplary fine scanning process in they-direction and collected data, respectively, for another exemplaryprocess/method for aligning the microfluidic assembly of the presentdisclosure.

FIGS. 24A and 24B illustrate an exemplary microfluidic chip at its finalaligned position and exemplary collected data, respectively.

In the description which follows, like parts are marked throughout thespecification and drawings with the same reference numerals,respectively. Drawing figures are not necessarily to scale and incertain views, parts may have been exaggerated for purposes of clarity.

DETAILED DESCRIPTION

The present disclosure relates to particle processing (e.g., cytometryincluding flow cytometry using drop sorters and microfluidic basedsorters, and/or cell purification) systems and methods that can operatein an autonomous fashion and, more particularly, to assemblies, systemsand methods for analyzing, sorting, and/or processing (e.g., purifying,measuring, isolating, detecting, monitoring and/or enriching) particles(e.g., cells, microscopic particles, etc.) where human intervention isnot required and/or is minimized.

The present disclosure provides improved particle processing (e.g.,cytometry and/or cell purification) systems and methods that can operatein an autonomous fashion (or in a substantially autonomous fashion). Ingeneral, the present disclosure provides for assemblies, systems andmethods for analyzing, sorting, and/or processing particles where humanintervention is not required or is minimized. Stated another way, thesystems, assemblies and methods of the present disclosure advantageouslyimprove run performance or operational characteristics of particleprocessing systems (e.g., cell purification systems, cytometers) bysignificantly reducing and/or substantially eliminating the burden ofoperation for human intervention by automating numerous functions,features and/or steps of the disclosed systems and methods.

In current practice, some of the challenges that arise when utilizing oroperating a particle processing system or assembly place many demandsand skill requirements on human operators to ensure run performance orinstrument operation. In general, run performance may be measured interms of: 1) the time taken to prepare a sample or the cytometer forinitiating measurements or sorting (including instrument start-up,calibration, preparation, and/or the insertion of sample and any otherassociated components such as collection vessels); 2) the rate at whicha particular measurement and/or sort is performed (e.g., presentingsample to measurement region and obtaining required data set and/orisolated particle fraction); 3) the quality of run (e.g., sustainedcalibration and performance during a particular measurement or sortoperation), the efficiency of the process, the recovery and/or yield ofthe desired particles, the handling (and therefore state) of sample thatis in contact or used with the cytometer; 4) the reliability andaccuracy of obtaining data from the measurement; 5) the successfulidentification, enumeration, isolation, purification, enrichment and/orsorting of particles or particle populations; 6) the removal of inputand/or output samples; 7) the careful/controlled post-measurementcleaning procedures prior to running further samples or instrumentshut-down; and 8) the on-going monitoring of all system functionsrelated to preventative or unplanned maintenance or repair.

In exemplary embodiments, the present disclosure provides for improvedparticle processing (e.g., cytometry and/or cell purification) systemsand methods where for some or all of the particle processing steps humanintervention is not required or is minimized, thereby providing asignificant commercial and/or operational advantage as a result.

Operation in an autonomous or (substantially autonomous) fashion, wherehuman intervention is not required (or is substantially not required) isreferred to herein as “operatorless.” A process or subprocess that canoperate in an operatorless mode does not require a skilled operator anddoes not require decisions to be made based on a knowledge of theparticles being processed or of the inner workings of the system. Thus,for example, a system may be considered “operatorless” even if itrequires a user to periodically press a button or interact with systemin some way to continue the operatorless operation, to direct theresults to a specific computer storage location, to otherwise maintainthe status quo, or make other non-process specific, non-functional,non-characterizing, non-analytical and/or non-diagnostic decisions, orthe like. The present disclosure relates to particle processing systemsand methods that can operate in an operatorless fashion and, moreparticularly, to assemblies, systems, methods and steps associated withprocessing particles where human intervention is not substantivelyrequired.

Referring now to the drawings, and in particular to FIG. 1, there isillustrated a block diagram of an exemplary embodiment of a particleprocessing system 10 according to the present disclosure. In general,particle processing system 10 is configured, dimensioned and adapted foranalyzing, sorting, and/or processing (e.g., purifying, measuring,isolating, detecting, monitoring and/or enriching) particles (e.g.,cells, microscopic particles, etc.) or the like, and wherein humanintervention is not required and/or is minimized for some or all of theparticle processing steps.

For example, system 10 may be a cytometry and/or a cell purificationsystem or the like, although the present disclosure is not limitedthereto. It is noted that exemplary cytometry systems 10 can include,without limitation, drop sorters (e.g., droplet or continuous jetsystems) or the like, or microfluidic flow sorters (e.g., microfluidicchip based systems that do not form drops) or the like.

As shown in FIG. 1, system 10 includes at least one processor 14 (e.g.,a central automation processor or master processor). System 10 alsoincludes at least one display device 12 in communication with theprocessor 14. It is noted that processor 14 may be the main centralprocessing unit of system 10, or it may be an access point to system 10.Further, processor 14 may be a distributed processor.

In exemplary embodiments, system 10 includes a particle deliveryassembly 18, a signal source assembly 20, a particle analysis orprocessing region assembly 22, a particle collection assembly 24 and asignal detection assembly 26. Processor 14 is in communication withparticle delivery assembly 18, signal source assembly 20, particleanalysis region assembly 22, particle collection assembly 24 and/orsignal detection assembly 26. These assemblies may be physicalassemblies or groupings of physical subassemblies, functional assembliesor groupings of functional subassemblies, or a combination of physicaland functional subassemblies.

In general, system 10 includes at least one sensor assembly/member 16that is configured and adapted to sense or monitor at least oneoperational characteristic or processing feature of system 10 (e.g.,sense or monitor at least one characteristic or feature of particledelivery assembly 18, signal source assembly 20, particle analysisregion assembly 22, particle collection assembly 24 and/or signaldetector assembly 26). The at least one sensor assembly 16 may include aplurality of individual sensors or detectors. These individual sensorsor detectors may be distributed over any given assembly 18, 20, 22, 24,26 and have any functionality. The sensor assembly 16 is in signalcommunication (e.g., wired and/or wireless communication) with processor14.

Sensor assembly/member 16 may include by way of non-limiting examples,photodetectors and or imaging devices.

As shown in FIG. 1, processor 14 may be in communication with (e.g., oneor a plurality) keypads and/or user stations 11, third-party devices 13and/or additional processors or controllers 15. Moreover, processor 14may be capable of communication with a network or internet 17, and maybe capable of sending or receiving audio, video and/or data or the like.

Processor 14 is generally programmed and/or configured to monitor andchange as necessary (e.g., automatically change) one or more parametersof system 10 (e.g., of particle delivery assembly 18, signal sourceassembly 20, particle analysis region assembly 22, particle collectionassembly 24 and/or signal detector assembly 26) based on the one or moreoperational characteristics sensed by the one or more sensor members 16.More particularly, system 10 includes at least one sensor assembly 16adapted to sense or monitor at least one processing feature of theparticle delivery assembly 18, signal source assembly 20, particleanalysis region assembly 22, particle collection assembly 24 and/orsignal detector assembly 26. Processor 14 is generally configured andadapted to enable or facilitate system 10 to process particles in anoperatorless fashion (e.g., to automatically change one or moreparameters of system 10 based on the one or more operationalcharacteristics sensed by the one or more sensor members 16). Ingeneral, processor 14 is configured to transmit and/or receive signals(e.g., command and/or status signals) or the like to or from sensorassemblies 16 and/or particle delivery assembly 18, signal sourceassembly 20, particle analysis region assembly 22, particle collectionassembly 24 and/or signal detector assembly 26, in order to change thestatus and/or operating parameters of particle delivery assembly 18,signal source assembly 20, particle analysis region assembly 22,particle collection assembly 24 and/or signal detector assembly 26.Stated another way, processor 14 generally is in communication withsensors 16 and/or the components of system 10 for control and/orcommunication purposes.

For example, processor 14 may send command signals to a sensor assembly16 (e.g., based on an operational characteristic sensed by that sensor16) associated with particle delivery assembly 18 (and/or directly toassembly 18) to control and/or change the status or operating parameterof particle delivery assembly 18. Moreover, processor 14 may receivestatus signals from sensor assemblies 16 regarding the status of thecomponents of system 10 (e.g., status of signal detector assembly 26,etc.).

It is to be noted that each sensor assembly 16 may include or beassociated with a local processor and/or processing or control unit(e.g., signal processing control unit) or the like. As such, each sensorassembly 16 may be in communication with at least one component (e.g.,assembly 18) of system 10 for control and/or communication purposes(e.g., independent of and/or in conjunction with processor 14). Forexample, a processor and/or processing control unit local to and/orassociated with each sensor assembly 16 may send command signalsdirectly to a component (e.g., assembly 18) of system 10 to controland/or change the status or operating parameter of that component. Suchcommand signals may or may not be directed from processor 14, and may becommunicated to and/or from processor 14, although the presentdisclosure is not limited thereto. In exemplary embodiments, eachassembly 18, 20, 22, 24 and/or 26 may include a processor or the likethat may operate independent of and/or in conjunction with processor 14for control and/or communication purposes associated with the componentsof system 10.

In exemplary embodiments and as shown in FIG. 1, system 10 includes afirst sensor assembly 16 a that is configured and adapted to sense ormonitor at least one operational characteristic or processing feature ofthe particle delivery assembly 18, a second sensor assembly 16 b that isconfigured and adapted to sense or monitor at least one operationalcharacteristic or processing feature of the signal source assembly 20, athird sensor assembly 16 c that is configured and adapted to sense ormonitor at least one operational characteristic or processing feature ofthe particle analysis region assembly 22, a fourth sensor assembly 16 dthat is configured and adapted to sense or monitor at least oneoperational characteristic or processing feature of the particlecollection assembly 24, and a fifth sensor assembly 16 e that isconfigured and adapted to sense or monitor at least one operationalcharacteristic or processing feature of the signal detector assembly 26.As such, processor 14 may be configured and adapted to enable orfacilitate system 10 or certain aspects of system 10 to processparticles in an operatorless fashion based on the operationalcharacteristics sensed by the first, second, third, fourth and/or fifthsensor assemblies 16 a-e. It is to be noted that one or more sensorassemblies may be associated with each assembly 18, 20, 22, 24 and/or26. Further, it is to be noted that system 10 may have any number ofsensor assemblies 16 a-“n” in communication with processor 14.

As discussed further below, some of the operational characteristics thatmay be monitored/sensed (e.g., via sensors 16) and/or run/maintained inan operatorless fashion (e.g., via processor 14 and sensors 16) mayinclude, without limitation, the following aspects and/or or features ofthe components of system 10:

-   (i) instrument start-up (e.g., power sources; electrical sources;    laser sources; excitation sources; fluidics; air/vacuum; pumps;    detection system; processors/computers; sub-systems; safety    mechanisms; self-tests; self-calibration; self-diagnose issues;    self-identification of current state (e.g., readiness) for sorting;    communication of status);-   (ii) input sample (e.g., identification of input sample (what is it    for recording, traceability, acceptance, sequencing, measurement or    sorting) and/or input sample vessel; presence of sample; quantity of    sample at any given time);-   (iii) insertion of sample (e.g., initial insertion of sample to    system 10 (from or within container); running (flow) of sample;    regulation and/or control of sample flow and/or sample flow rate    dynamically (periodically and/or to a set-point that is defined    automatically or in advance during instrument    set-up/manufacture/calibration); monitoring sample volume or level;    monitoring event rate and altering sample pressure and/or expulsion    rates to achieve a desired set-point for particle event (input)    rate);-   (iv) sort collection (e.g., vessel insertion/removal; position of    vessels (waste, sorted fraction) or of unitary cartridge; sealing of    fluidic and/or other necessary connections required to enable system    10 operation; identification and/or selection of particles or    particle populations of interest for measurement and/or sorting);-   (v) sort mode and/or automated adjustment/alignment of operating    conditions (e.g., to enable predefined/user specified    purity/efficiency and/or recovery/yield modes (event rate, gating    schemes, sort rate, abort rate, peak-to-valley ratio); applying    various data manipulation algorithms to calculate and/or    automatically adjust data that may be visualized as a rotation or    other translation function on one or more dimensions on data sets    and/or on bivariate data plots to assist with the projection of data    in histogram views; adjustment of parameters to bring particle    population within acceptable signal limits to enable reliable    measurement of particles or to enable certain data to be displayed    visually (sensitivity/gain/position and/or photodetector    amplification) using software/firmware or hardware);-   (vi) monitoring of particle clusters/populations and/or cluster    positions based on certain data representations (e.g., monitor and    then adjust data/sort region conditions or boundaries (tracking) to    account for minor fluctuations in measured signal levels so that    sorting (particle processing) may continue with minimal impact on    sort purity and recovery);-   (vii) adjusting a sort mechanism (e.g., sort monitor and/or drop    monitor and/or side streams/calibration/timing and/or particle/drop    trajectory and/or velocity and expected arrival at sort    position/mechanism to enable reliable/reproducible/stable    performance of particle separation to meet the desired outcome (such    as given number of particles, purity, ratio, recovery, yield,    characteristic property, homogeneity, heterogeneity, size,    morphology, fluorescence, light scatter properties, DNA content, and    the like);-   (viii) adjusting optical measurement apparatus (e.g., through    positioning various mechanical or optical components, or by    effecting the direction or position of one or more optical paths or    particle paths to enable reliable and consistent measurement and/or    sorting of particles flowing within system 10 (e.g., within or    associated with the cytometer apparatus);-   (ix) monitor and control functions (e.g., system leaks (gas/liquid);    out-of-bounds (power, safe shut-down, universal power supply, safety    and control network, etc.); trending (e.g., sample quality, sort    rate, sort fraction, assessment of live to dead cell ratio within a    sample, scheduling of samples, alarm conditions and alarms);    intelligent error handling such as self-fixing, self-regulation or    other act such as by reacting to system 10 parameters (e.g.,    temperature, pressure, vacuum, alignment movement, etc.) and/or    parameter changes that may affect system operation);-   (x) various alerts and/or alarms (e.g., alerts/alarms that caution    device/user that system is nearing or operating outside acceptable    limits; run and control fluid (sheath, waste, sample, sort fraction    and trajectory of sort and non-sort fractions) level monitor and    refill; cleaning lines; sample waste; etc.);-   (xi) safety aspects (e.g., safety of environment or environment of    operator or sample or system/instrument); potential exposure of    sample to the environment, the apparatus, and other samples;-   (xii) automated and/or robotic feeding of samples, sheath fluid(s),    sort output fractions, waste and other required fluids, consumables,    calibration parts, cleaning supplies, etc. (e.g., systems/methods to    enable continuous operation over extended periods (e.g., for    different samples) without the need for human intervention);-   (xiii) remote-controlled features and/or operations (e.g., reduce    requirement for operator to be in front of system 10, system 10    could be controlled from a remote location/room with respect to the    system 10; remote-controlled features that may be particularly    useful if there are concerns over sample contamination issues    (between samples, or sample and system/environment, or sample and    operator, as non-limiting examples), or concerns where pathogens,    communicable diseases, or the like or other vectors are involved    (e.g., Hepatitis C, Influenza strains, Malaria, H1N1, HIV, BSE, TB,    etc.));-   (xiv) other aspects or features of system 10 (e.g., nozzle    alignment; laser alignment; excitation source alignment; detector    alignment; data manipulation for identification and zooming;    population identification; population sort regions; set-point    purity; etc.);-   (xv) auto-rotation and/or translation (e.g., calculating and    automatically adjusting data rotation on one or more bivariate plots    to assist with projection of data in histogram views and related    gating or sort strategies; adjusting fluorescence compensation    parameters);-   (xvi) fluidic stability (e.g., monitoring droplet break-off image    and automatically adjusting amplitude and phase controls to maintain    position and profile/shape at neck of last attached drop);-   (xvii) sort timing (e.g., determine droplet break-off or timed    microfluidic actuation/switch delay without the need for user    intervention);-   (xviii) sample flow rate (e.g., monitoring event rate and    controlling sample pressure to achieve a desired set-point for    particle event rate);-   (xix) optical alignment of jet or microfluidic channel (e.g.,    image-based alignment of nozzle and/or excitation source to    predefined position where image is adjusted with respect to expected    conditions);-   (xx) data-based alignment (e.g., data-based alignment of nozzle,    microfluidic chip channel(s), excitation source(s) and/or detector    position(s) using feedback from measured photodetector signals    (e.g., from calibration or target particles; identify and locate    sort regions around desired cell or other particle populations)    (Non-limiting examples include: using system 10 for the sorting of    sperm by measuring DNA content to identify and isolate X- and/or    Y-chromosome-bearing sperm; isolating cells for human therapeutic    applications such as those isolated using immunophenotypic,    internal, surface, markers or other intrinsic characteristics;    isolating cells in industrial processes, or in life science    research, where cells can be identified and selected based on    intrinsic characteristics, or some other attribute following a    sample preparation step (such as by adding a stain as a non-limiting    example)); and/or-   (xxi) sort stream path and/or trajectory (e.g., determine droplet    deflection conditions such as position, fanning, charge timing,    waste centering, etc.).

The present disclosure will be further described with respect to thefollowing examples; however, the scope of the disclosure is not limitedthereby. The following examples illustrate the systems and methods ofthe present disclosure of analyzing, sorting, and/or processing (e.g.,purifying, measuring, isolating, detecting, monitoring and/or enriching)particles (e.g., cells, microscopic particles, etc.) or the like in anautonomous fashion.

Example 1: Drop Sorter Particle Processing System

Referring again to the drawings, and in particular to FIG. 2, there isillustrated a block diagram of another exemplary embodiment of aparticle processing system 100 according to the present disclosure.Similar to system 10, particle processing system 100 is configured,dimensioned and adapted for analyzing, sorting, and/or processing (e.g.,purifying, measuring, isolating, detecting, monitoring and/or enriching)particles (e.g., cells, microscopic particles, etc.) or the like, andwherein human intervention is not required or is minimized.

For example, system 100 may be a cytometry and/or a cell purificationsystem or the like, although the present disclosure is not limitedthereto. In exemplary embodiments, system 100 is a drop sorter particleprocessing system 100 (e.g., a cytometer system; a droplet or continuousjet system, etc.) or the like. Exemplary drop sorter particle processingsystems/components are disclosed, for example, in U.S. Pat. Nos.8,277,764; 7,012,689; 6,372,506 and 6,248,590; and U.S. PatentPublication Nos. 2012/0200857 and 2012/0202237; the foregoing beingincorporated herein by reference in their entireties.

Similar to system 10 and as shown in FIG. 2, system 100 includes atleast one processor 114 (e.g., a central automation processor or masterprocessor). At least one display device 112 is in communication withprocessor 114. Processor 114 may also be in communication with (e.g.,one or a plurality of) keypads and/or user stations 111, third-partydevices 113 and/or additional processors or controllers 115. Processor114 may be capable of communication with a network or internet 117, andmay be capable of sending and/or receiving audio, video and/or data orthe like.

In exemplary embodiments, system 100 includes a particle deliveryassembly 118, the particle delivery assembly 118 generally configuredand dimensioned to deliver a stream 136 containing particles or the liketo a particle inspection region assembly 122 (FIGS. 2-3). System 100also includes signal source assembly provided as an electromagneticradiation source assembly 120, a particle collection assembly 124 and asignal detector/detection assembly 126. Processor 114 is incommunication with particle delivery assembly 118, electromagneticradiation source assembly 120, particle inspection region assembly 122,particle collection assembly 124 and/or signal detector assembly 126.

Like system 10, particle processing system 100 includes at least onesensor assembly/member 116 that is configured and adapted to sense ormonitor at least one operational characteristic or processing feature ofsystem 100 (e.g., sense or monitor at least one characteristic orfeature of particle delivery assembly 118, electromagnetic radiationsource assembly 120, particle inspection region assembly 122, particlecollection assembly 124 and/or signal detector assembly 126). Eachsensor assembly 116 a-“n” may be in communication with (e.g., electricalcommunication, wireless communication, etc.) and/or operatively coupledto processor 114. System 100 may include a plurality of sensorassemblies 116 a-e.

Referring to FIGS. 2 and 3, it is to be noted that system 100 may be adroplet sorter system or the like, and may include a processor 114, aplurality of assemblies 118, 120, 122, 124 and/or 126, and a pluralityof sensors 116 a-“n”. Further, system 100 may be a multi-nozzled dropletsorter system or the like, and may include a plurality of processors114, a plurality of any or all of the assemblies 118, 120, 122, 124,126, and a plurality of any or all of the sensors 116 a-“n”.

In general, processor 114 is configured to change or adjust one or moreparameters, features, characteristics and/or components of system 100based on the one or more operational characteristics sensed by the oneor more sensor members 116. In certain embodiments, a modicum of inputmay be requested of an operator. In certain preferred embodiments,system 100 may be configured to automatically change or adjust one ormore parameters, features, characteristics and/or components based onthe one or more operational characteristics sensed by the one or moresensor members 116. As such, processor 114 may generally be configuredand adapted to enable or facilitate system 100 to process particles orto perform certain particle processing steps in an operatorless fashion.

In general, processor 114 is configured to transmit or receive signals(e.g., command/status signals) or the like to/from sensor assemblies 116a-e and/or particle delivery assembly 118, electromagnetic radiationsource assembly 120, particle inspection region assembly 122, particlecollection assembly 124 and/or signal detector assembly 126, in order tochange the status and/or operating parameters of particle deliveryassembly 118, electromagnetic radiation source assembly 120, particleinspection region assembly 122, particle collection assembly 124 and/orsignal detector assembly 126. Stated another way, processor 114 is incommunication with sensors 116 a-e and/or the components of system 100for control and/or communication purposes.

For example, processor 114 may send command signals to a sensor assembly116 a associated with particle delivery assembly 118 (and/or directly toa component within particle delivery assembly 118 to control anoperating parameter of the particle delivery assembly 118. Moreover,processor 114 may receive status signals from sensor assemblies 116 a-eregarding the status of the components of system 100.

Each sensor assembly 116 may include or be associated with a localprocessor and/or processing control unit (e.g., signal processingcontrol unit) or the like. As such, each sensor assembly 116 may be incommunication with at least one component (e.g., assembly 118) of system100 for control and/or communication purposes (e.g., independent ofand/or in conjunction with processor 114). For example, the processor orcontrol unit local to and/or associated with each sensor assembly 116may send command signals directly to a component (e.g., assembly 118) ofsystem 100 to control an operating parameter of that component. Suchcommand signals may or may not be directed from processor 114, and maybe communicated to and/or from processor 114, although the presentdisclosure is not limited thereto. In exemplary embodiments, eachassembly 118, 120, 122, 124 and/or 126 can include a local processor orthe like that can operate independent of and/or in conjunction withprocessor 114 for control and/or communication purposes associated withthe components of system 100.

Processor 114 and/or sensors 116 a-e may advantageously be configuredand adapted to enable or facilitate system 100 or certain aspects ofsystem 100 to process particles in an operatorless fashion based on theoperational characteristics sensed by the sensor assemblies 116 a-e.Again, system 100 may have any number of sensor assemblies 116 a-“n” incommunication with processor 114.

Turning now to FIG. 3, an example of a drop sorter particle processingsystem 100 or the like is illustrated as a drop cytometer system 100(e.g., jet-in-air flow cytometer system), although the presentdisclosure is not limited thereto. Rather, it is noted that the systemsand methods described may be applied to other particle processingsystems.

As noted above, exemplary system 100 includes a particle and/or fluiddelivery assembly 118. Assembly 118 may include a nozzle 132 having anozzle orifice 134 for delivering a fluid stream 136 to a particleinspection region 122 proximal to radiation source assembly 120.

The fluid stream 136 may be perturbed into droplets 138 by an oscillator140. The droplets 138 may pass through an electromagnetic field producedby deflection plates 142 of particle collection assembly 124. Inexemplary embodiments, a charge applied to each droplet 138 defines apath into one of one or more collection containers or members 144 ofparticle collection assembly 124.

In certain embodiments, the fluid stream 136 may define a substantiallycoaxial fluid stream having an inner core stream of sample or particles146 and an outer stream of sheath fluid 148. The particles may be singlecell organisms such as bacteria or individual cells in a fluid, such asvarious blood cells, sperm or nuclei derived from tissue. Depending onthe application the particles may be stained with a variety of stains,probes, or markers selected to differentiate particles or particlecharacteristics. Some stains or markers only bind to particularstructures, while others, such as DNA/RNA dyes, may bind in some mannerto nuclear DNA or RNA. The particles may be stained with a fluorescentdye which emits fluorescence in response to an excitation source. As onenon-limiting example, sperm may be stained with Hoechst 3334 which bindsto X-chromosomes and Y-chromosomes. U.S. Pat. Nos. 5,135,759 and7,758,811 describe exemplary methods for staining sperm, and are eachincorporated herein by reference.

In oriented sperm, the relative quantity of Hoechst 33342 can bedetermined providing means for differentiating X-chromosome bearingsperm from Y-chromosome bearing sperm. Additionally, certain embodimentsare envisioned to work with DNA sequence specific dyes and sex specificdyes.

The fluid stream 136 may exit the nozzle orifice 134 with increasinglypronounced undulations 104 or decreasing neck 106 thicknesses in adownstream direction until a break off point 150 is reached wheredroplets 138 break away from the fluid stream 136. The break off point150 is illustrated as the substantially last point at which a droplet138 contacts the fluid stream 136. In general, this location representsthe last point in time a charge may be applied to a droplet 138, as ameans for providing a physical sort mechanism.

Radiation source assembly 120 may include an excitation energy source152 for providing energy (e.g., a laser, a light emitting diode, or anarc lamp, as non-limiting examples) to the fluid stream 136 andparticles of interest contained in the sample 146. In exemplaryembodiments, the excitation energy source 152 is aligned with aninspection zone 154 on the fluid stream 136 for interrogating particlesas they pass the inspection zone 154 of particle inspection region 122.It is noted that the inspection zone 154 may be located downstream ofthe nozzle orifice 134, may be located within a cuvette, or may belocated a flow chamber upstream or downstream of the nozzle orifice 134.

Reflected and/or emitted electromagnetic radiations from the fluidstream 136 and particles in the fluid stream 136 can be collected by adetector or sensor assembly 156 of signal detector assembly 126. Thedetector assembly 156 may include any number of detectors or devicesconfigured in the forward, side, and/or back direction relative to theexcitation energy source 152. For example, assembly 126 may utilizevarious optics (e.g., filters, mirrors, dichroic mirrors, splitters, andother reflective and/or refractive elements, etc.) to detectelectromagnetic radiation at any number of wavelengths and/or in anynumber of directions and in a variety of combinations.

In exemplary embodiments, detected signals may be processed for theclassification of particles within the fluid stream 136, and sortdecisions may be made at a controller 158. Controller 158 may be a localcontroller associated with the signal detector assembly 126. Thecontroller 158 may include acquisition and sort electronics in the formof analog and/or digital components for processing signals from thedetector assembly 156 and applying a sort logic. Once a sort decision ismade, the controller 158 may send a signal to a charge device to charge(or not charge) the fluid stream 136 through the sample 146 in thenozzle 132 so that the droplets 138 are deflected (or are not deflected)by deflection plates 142 into the appropriate container 144.

In general, the timing at which the appropriate charge is applied to thefluid stream 136 should closely match to the time a particle of interestis in a droplet 138′ at the break off point 150 in order to ensure anaccurate sort action. Further, a drop delay value (DDV) may bedetermined from when the particle of interest in detected in thedetection zone 154 to when it is located in the droplet 138′ at thebreak off point 150. In exemplary embodiments, an imaging assembly 102may be provided to monitor or update the distance between the break offpoint 150 and the inspection zone 154 and to determine, monitor andupdate the number of undulations 104 in the fluid stream 136 to predicta current or updated drop delay value. Such drop delay information maythen be communicated or transmitted to sensor assembly or assemblies 116and/or to processor 114 for control and/or communication purposes.

For example, in one embodiment the imaging assembly 102 may include anoptical system 160 and a sensing element 162 for capturing an image 166of the fluid stream 136 for the purpose of modifying or detecting theappropriate drop delay value for accurate sort decisions. The sensingelement 162 (e.g., a charge coupled device) may be capable of convertingan image into a series of electrical or digital signals. Other sensorsand configurations for detecting the light intensity of an image in highresolution may also be used (e.g., a photodiode array or a sensorarray). A strobe 164 or the like may illuminate the fluid stream 136 atpredicted intervals to create an image of the fluid stream 136 asphotons interacting with the object of the fluid stream 136. The opticalsystem 160 may include a series of optical elements for manipulating theimage 166 of the fluid stream 136. As one example, the optical system160 may comprise multiple lenses or multiple mirrors, other reflectiveor refractive elements, and combinations of different reflective andrefractive elements.

In one embodiment, the optical system 160 in operation may manipulatethe aspect ratio of the image 166 of the fluid stream 136, such ascompressing the length of the fluid stream and/or expanding the width ofthe fluid stream, as disclosed and described in U.S. Patent PublicationNo. 2012/0200857, the content of which is hereby incorporated byreference in its entirety. By manipulating the aspect ratio to form amanipulated image of the fluid stream, exemplary optical system 160 mayserve to acquire and preserve relevant information pertaining to thedrop delay value. Such an optical system 160 for modifying an image of afluid stream 166 may provide, in a single image, enough information todetermine or modify drop delay values. In exemplary embodiments, suchinformation may be communicated to sensor assembly or assemblies 116and/or to processor 114 for control and/or communication purposes.However, it is to be noted that optical system 160 and/or imagingassembly 102 may take a variety of other forms and/or be utilized for avariety of other steps, features, or functions, as discussed furtherbelow.

The optical system 160 and/or imaging assembly 102 of assembly 126 mayhave its own processor or the like that is configured, programmed andadapted to monitor and/or control (independent of and/or in conjunctionwith processor 114) the operational characteristics or features of atleast one component of system 100 (e.g., of assembly 126). In certainembodiments, optical system 160 and/or imaging assembly 102 of assembly126 may have its own processor in communication with processor 114 andmay make changes based on instructions received from processor 114 (orbased on monitored characteristics of at least one sensor 116 of system100).

As noted above and as shown in FIG. 3, particle processing system 100includes at least one sensor assembly/member 116 that is configured andadapted to sense or monitor at least one operational characteristic orprocessing feature of system 100. In exemplary embodiments, system 100includes a plurality of sensor assemblies 116 a-“n”. In certainembodiments and as shown in FIG. 2, system 100 includes a first sensorassembly 116 a that is configured and adapted to sense or monitor atleast one operational characteristic or processing feature of theparticle delivery assembly 118, a second sensor assembly 116 b that isconfigured and adapted to sense or monitor at least one operationalcharacteristic or processing feature of the electromagnetic radiationsource assembly 120, a third sensor assembly 116 c that is configuredand adapted to sense or monitor at least one operational characteristicor processing feature of the particle inspection region 122, a fourthsensor assembly 116 d that is configured and adapted to sense or monitorat least one operational characteristic or processing feature of theparticle collection assembly 124, and a fifth sensor assembly 116 e thatis configured and adapted to sense or monitor at least one operationalcharacteristic or processing feature of the signal detector assembly126. It is noted that system 100 may have any number of sensorassemblies 116 a-“n” in communication with processor 114.

Exemplary processor 114 is configured to transmit and/or receive signals(e.g., command and status signals) or the like to and/or from sensorassemblies 116 and/or particle delivery assembly 118, electromagneticradiation source assembly 120, particle inspection region 122, particlecollection assembly 124 and/or signal detector assembly 126, in order tochange the status and/or operating parameters of the components ofsystem 100. In short, processor 114 is in communication with sensors 116and/or the components of system 100 for control and/or communicationpurposes. As such, exemplary processor 114 is configured and adapted toenable or facilitate system 100 to process particles in an operatorlessfashion based on the operational characteristics sensed by the sensorassemblies 116.

In general, sensor assembly 116 a associated with particle deliveryassembly 118 may be configured to sense or monitor at least onecharacteristic or feature of nozzle 132, nozzle orifice 134, oscillator140, sample 146, sheath fluid 148 and/or the fluid delivery system(e.g., pumps, reservoirs, valves, tubing, etc.) of particle deliveryassembly 118 so that processor 114 may monitor and/or change one or moreparameters or characteristics of assembly 118 based on the sensed ormonitored features to enable assembly 118 to operate in an operatorlessfashion.

For example and without limitation, sensor assembly 116 a associatedwith particle delivery assembly 118 may sense or monitor such exemplarycharacteristics or features of nozzle 132, oscillator 140, sample 146,sheath fluid 148 and/or other components of particle delivery assembly118 and/or system 100 including: appropriate pressure levels, pumpspeeds, vacuum levels, sample 146 characteristics, sheath fluid 148characteristics, waste status and control, stability, alignmentadjustment issues, flow rates, identifications, durations, presence(e.g., of sample 146 and/or sheath fluid 148), insertion (e.g., ofsample 146 and/or sheath fluid 148), removal (e.g., of sample 146 and/orsheath fluid 148), replacement and/or temperatures. Likewise, sensorassembly 116 b associated with electromagnetic radiation source assembly120 may sense or monitor such exemplary characteristics or features ofenergy source 152 and/or other components of electromagnetic radiationsource assembly 120/system 100 including, without limitation:appropriate power, intensity, beam size, wavelength, position, stabilityand/or motion.

Similarly, sensor assembly 116 c associated with particle inspectionregion assembly 122 may sense or monitor such exemplary characteristicsof droplets 138, stream 136 and/or other components of particleinspection region 122 and/or system 100 including, without limitation:monitoring the stream, monitoring drop formation, and/or determiningsort timing.

Furthermore, sensor assembly 116 d associated with particle collectionassembly 124 may sense or monitor such exemplary characteristics ofdeflection plates 142, droplets 138, collection members 144 and/or othercomponents of particle collection assembly 124 and/or system 100including, without limitation: appropriate sort control (e.g.,amplitude, charge, rate if charging, etc.), appropriate deflection,stream stability, non-spraying, direction, insertion (e.g., of members144), identification, removal (e.g., members 144), level monitor (144,146, 148), volume presence, optical alignment and/or position, timeand/or duration, number of sorted drops, particles and/or cells, purity,yield and/or recovery.

Also, sensor assembly 116 e associated with signal detector assembly 126may sense or monitor such exemplary characteristics of detector assembly156, controller 158, imaging assembly 102, optical system 160 and/orother components of signal detector assembly 126 and/or system 100including, without limitation: alarms, progress, safety, instrumentstart-up, optical alignment, direction, position, and/or monitor and/orcontrol functions.

In general, processor 114 is configured to monitor and adjust (e.g.,automatically change) one or more parameters, features, characteristicsand/or components of system 100 based on the one or more operationalcharacteristics sensed by the one or more sensor members 116. As such,processor 114 is generally configured and adapted to enable orfacilitate system 100 to process particles in an operatorless fashion.

In exemplary embodiments, other operational characteristics or featuresof the components of system 100 that may be monitored or sensed (e.g.,via sensors 116) and/or run in an operatorless fashion (e.g., viaprocessor 114 and sensors 116) may include, without limitation, thefollowing:

-   (i) instrument start-up (e.g., power sources; electrical sources;    laser sources (laser 152 may switched on automatically to ensure it    has warmed up or reached equilibrium state prior to use, may be    remotely controlled, or may be controlled based on some other    condition); excitation sources; fluidics (sample 146, sheath 148);    air/vacuum; pumps; detection system (assembly 156);    processors/computers; sub-systems; safety mechanisms; self-tests;    self-calibration; self-diagnose issues; self-identification of    current state (e.g., readiness) for sorting; communication of    status);-   (ii) input sample (e.g., identification of input sample 146 (what is    it for recording, traceability, acceptance, sequenced, measurement    or sorting) and/or input sample vessel; presence of sample 146;    quantity of sample 146 at any given time);-   (iii) insertion of sample 146 (e.g., initial insertion of sample 146    to system 100 (from or within container); running (flow) or pausing    of sample 146; regulation and/or control of sample flow and/or    sample flow rate dynamically (periodically and/or to a set-point    that is defined automatically or in advance during instrument    set-up/manufacture/calibration); monitoring sample volume or level;    monitoring event rate and altering sample pressure and/or expulsion    rates to achieve a desired set-point for particle event (input)    rate);-   (iv) sort collection (e.g., vessel 144 insertion/removal; position    of vessels 144 (waste, sorted fraction(s)) or of unitary cartridge;    sealing of fluidic and/or other necessary connections required to    enable system 100 operation; identification and/or selection of    particles or particle populations of interest for measurement and/or    sorting (the identification and/or location of sort gates on desired    particle population); the automated placement of sort regions on or    around live, suitably oriented or aligned, or other characteristics    of cell populations or of other particles (e.g., identify live and    dead populations, identify oriented or aligned fractions, apply    conditioning such as data manipulation, rotation, translation, zoom,    identify cell or other particle populations, create sort gate with    suitable geometry to ensure desired purity, recovery, enrichment,    efficiency and/or sort rate. Applying appropriate signal and/or    electrical gain to move or maintain population within acceptable    signal range, field of view, and/or region of interest);-   (v) sort mode and/or automated adjustment or alignment of operating    conditions (e.g., to enable predefined/user specified    purity/efficiency and/or recovery/yield modes (event rate, gating    schemes, sort rate, abort rate, peak to valley ratio, etc.);    applying various data manipulation algorithms to calculate and/or    automatically adjust data that may be visualized as a rotation or    other translation function on one or more dimensions on data sets    and/or on bivariate data plots to assist with the projection of data    in histogram views; adjustment of parameters to bring particle    population within acceptable signal limits to enable reliable    measurement of particles or to enable certain data to be displayed    visually (sensitivity/gain/position and/or photodetector    amplification) using software/firmware or hardware (examples include    adjust photodetector voltage and/or gain (until population is in    desired location), optical alignment functions enabled (excitation    source and/or associated optical and/or mechanical elements, flow    chamber (particles), detectors) using particles/mimic particles or    other optical schemes such as light sources/image processing/machine    vision));-   (vi) monitoring of particle clusters/populations and/or cluster    positions based on certain data representations (e.g., monitor and    then adjust data/sort region conditions or boundaries (tracking) to    account for minor fluctuations in measured signal levels so that    sorting (particle processing) may continue with minimal impact on    sort purity and recovery);-   (vii) adjusting a sort mechanism (e.g., sort monitor and/or drop    monitor and/or side streams/calibration/timing and/or particle/drop    trajectory and/or velocity and expected arrival at sort    position/mechanism to enable reliable/reproducible/stable    performance of particle separation to meet the desired outcome (such    as given number of particles, purity, ratio, recovery, yield,    characteristic property, homogeneity, heterogeneity, size,    morphology, fluorescence, light scatter properties, DNA content, and    the like));-   (viii) adjusting optical measurement apparatus (e.g., through    positioning various mechanical or optical components, or by    effecting the direction or position of one or more optical paths or    particle paths to enable reliable and consistent measurement and/or    sorting of particles flowing within or associated with system 100);-   (ix) monitor and control functions (e.g., system leaks (gas/liquid);    out of bounds (power, safe shut-down, universal power supply, safety    and control network, etc.); trending (e.g., sample quality, sort    rate, sort fraction, assessment of live to dead ratio within a    sample, scheduling of samples, alarm conditions and alarms);    intelligent error handling such as self-fixing, self-regulation or    other act such as by reacting to system 100 parameters (e.g.,    parameter change such as temperature, pressure, vacuum, alignment    movement, etc.) that may affect system/instrument operation);-   (x) alerts and/or alarms (e.g., alerts or alarms that caution device    or user that system is nearing or operating outside acceptable    limits/window; run and control fluids (sheath, waste, sample, sort    fraction and trajectory of sort and non-sort fractions) level    monitor and refill; cleaning lines; sample waste; etc.);-   (xi) safety aspects (e.g., safety of environment or from environment    of operator or sample or system/instrument); potential exposure of    sample to the environment, the apparatus, and other samples;    automated and/or robotic feeding of samples, such as sheath fluid(s)    148, sort output fractions, waste and other required fluids,    consumables, calibration parts, cleaning supplies, etc. (e.g.,    systems/methods to enable continuous operation over extended periods    (e.g., for different samples 146) without the need for human    intervention);-   (xii) remote-controlled features and/or operations (e.g., reduce    requirement for operator to be in front of system 100, system 100    could be controlled from a remote location/room with respect to the    system 100; remote-controlled features that may be particularly    useful if there are concerns over sample contamination issues    (between samples, or sample and system/environment, or sample and    operator, as non-limiting examples), or concerns where pathogens,    communicable diseases or the like or other human or non-human    vectors are involved (e.g., Hepatitis C, Influenza strains, Malaria,    H1N1, HIV, BSE, TB, etc));-   (xiii) other aspects or features of system 100 (e.g., nozzle 132    alignment; laser 152 alignment; excitation source 152 alignment;    detector 156 alignment; data manipulation for identification and    zooming; population identification; population sort regions;    set-point purity; etc.);-   (xiv) auto-rotation (e.g., calculating and automatically adjusting    data rotation on one or more bivariate plots to assist with    projection of data in histogram views and related gating or sort    strategies);-   (xv) fluidic stability (e.g., monitoring droplet 138 break-off image    and automatically adjusting amplitude and phase controls to maintain    position and profile/shape at neck of last attached drop 138);-   (xvi) sort timing (e.g., determine droplet 138 break-off without the    need for user intervention);-   (xvii) sample flow rate (e.g., monitoring event rate and controlling    sample pressure to achieve a desired set-point for particle event    rate);-   (xviii) optical alignment of jet (e.g., image-based alignment of    nozzle 132 and/or excitation source 152 to predefined position where    image is adjusted with respect to expected conditions);-   (xix) data-based alignment (e.g., data-based alignment of nozzle    132, excitation source 152 and/or detector 156 position using    feedback from measured photodetector signals (e.g., from calibration    or target particles; identify and locate sort regions around cell or    other particle populations));-   (xx) sort stream (e.g., determine droplet 138 deflection conditions    such as position, fanning, charge timing, waste centering, etc.);    and/or-   (xxi) event rate (e.g., monitoring event rate and controlling sample    pressure to achieve a desired set-point for particle event rate).

Moreover, the processor 114 and sensor assemblies 116 of the presentdisclosure may be advantageously utilized to sense/monitor even othercharacteristics/aspects of system 100, including, for example, othercharacteristics/aspects disclosed and described in U.S. Pat. Nos.8,277,764; 7,012,689; 6,372,506 and 6,248,590; and U.S. PatentPublication Nos. 2012/0200857 and 2012/0202237; each incorporated byreference herein in their entirety.

Exemplary Determination of Particle Sub-Populations:

In certain embodiments, system 100 may be configured to automaticallydetermine one or more cell or particle sub-populations. Referring toFIGS. 4A and 4B, cell populations may be displayed, for example, on oneor more bivariate plots (e.g., side scatter versus fluorescence; areaversus peak; etc.). Previously, an operator would define a gating regionthat enclosed a cell sub-population of interest by drawing an enclosedregion on the bivariate plot around a cell sub-population of interest.The gating region, for example, to define sub-populations for sorting,would be selected based on an understanding of the expectedcharacteristics of the cell population and the experience of theoperator in applying selection criteria to the expected characteristicsof the cell population. Thus, for example, the cells of interest may beknown reside in a region of the bivariate plot having strong sidescatter signals and strong fluorescence signals. When a sub-populationor cluster of cells exhibiting these predetermined characteristics couldbe discerned, the operator would draw a gate that would surround thesecells. An experienced operator would select and draw the gating regionto exclude unwanted cells and/or include desired cells. Should thegating region be drawn too broadly then unwanted cells may beundesirably included in the sorted sub-population. Should the gatingregion be drawn more specifically then purity of the sortedsub-population may be enhanced but yield may be undesirably decreased.Thus, the size, shape, orientation, perimeter, etc. of the gating regionaffect both the purity and the yield of the sorted sub-population.

In exemplary embodiments of system 100, cell sub-populations may beidentified and/or gating regions may be automatically drawn based onmeasured or sensed characteristics of the cells and selection criteria.For example, a cell population may be identified based on a firstcharacteristic, such as a light scatter or fluorescence signal. A firstcharacteristic sub-population of cells may be identified as those cellshaving a first measured or sensed characteristic that satisfies a firstselection criteria, e.g., predetermined upper and/or lower thresholds ofthis first characteristic. A statistical analysis of the firstcharacteristic sub-population may be conducted to determine itsdistribution and/or other attributes of interest.

The statistical analyses may be used to further refine the firstcharacteristic sub-population of cells. The cell population may also beidentified based on a second characteristic, such as a scatter orfluorescence signal. A second characteristic sub-population of cells maybe identified as those cells having a second measured or sensedcharacteristic that satisfies a second selection criteria, e.g.,predetermined threshold(s) of this second characteristic. A statisticalanalysis of the second characteristic sub-population may be conducted todetermine its distribution and/or other attributes of interest. Thestatistical analyses may be used to further refine the secondcharacteristic sub-population of cells. A combined sub-population ofcells satisfying both the first selection criteria and the secondselection criteria may be defined. A statistical analysis of thecombined sub-population of cells may be conducted to determine itsdistribution and/or other attributes of interest. The statisticalanalyses of the combined sub-population of cells may be used to furtherrefine the combined sub-population of cells. Optionally, third, fourth,etc. measured or sensed characteristics may be used identifysub-populations and/or refined the sub-populations.

A characteristic used to identify a particular sub-population of cells(or particles) may be provided as a number or a quantitative value(relative or absolute), as a percentage, as a difference, as a ratio, asa mathematical equation or algorithm, as a look-up table, as astatistical event, as a function of another characteristic, as acombination thereof, etc.

According to some embodiments, a particular sub-population of cells maybe defined based on a first set of measured, sensed and/or determinedcharacteristics of the cells satisfying a first set of selectioncriteria. As a non-limiting exemplary embodiment, a sub-population ofcells may be defined as those cells having a scatter signal intensityabove a predetermined scatter threshold and a fluorescence signalintensity above a predetermined fluorescence threshold. Upper thresholdsmay also be predetermined and applied as a condition for inclusionwithin the sub-population of cells. These predetermined thresholds maybe absolute and/or relative values. For example, the predeterminedscatter lower threshold may be set at a value equal to 70% of the sidescatter range for the entire population.

The cells falling within this first sub-population, as determined usingthe first set of measured, sensed and/or determined characteristics, maythen be subjected to a second set of measured, sensed and/or determinedcharacteristics of the cells satisfying a second set of selectioncriteria so as to further be sub-grouped. As a non-limiting exemplaryembodiment, a sub-grouping of the sub-population of cells may be definedas those cells having an area under a fluorescence signal above apredetermined area threshold and/or a peak fluorescence intensity signalvalue above a predetermined peak intensity threshold. Upper thresholdsmay also be predetermined and applied as a condition for inclusionwithin the sub-group of the sub-population of cells. These predeterminedthresholds may be absolute and/or relative values. For example, thepredetermined area lower threshold may be set to a value equal to themean area of the fluorescence signal for the entire sub-population.

Thus, it is understood that selection of cell populations of interestmay be a multi-step process using any of various measured, sensed and/ordetermined characteristics and predetermined threshold or otherselection criteria.

According to certain embodiments, for a multi-channel particleprocessing system, the selection criteria for particles or cells flowingthrough any single micro-fluidic channel may be based on real-time datafrom other micro-fluidic channels in the particle processing system.Thus, for example, a selection criteria may require that a particle'ssignal fall within a standard deviation (or any other measurementcriteria) of the mean of all particles flowing through the plurality ofmicro-fluidic channels that meet a lower threshold. This mean value maybe calculated over a certain time interval, over a certain number ofparticle events, and/or a combination thereof.

Exemplary Determination of Gating Regions:

According to certain aspects, and referring to FIG. 4B, gating regionsmay be automatically defined around the sub-populations and/orsub-groups of cells. Predetermined gating selection criteria may be usedto draw a gating region around the combined sub-population. For example,a gating region may be defined to include 100% of the combinedsub-population. Optionally, a gating region may be defined to includethat portion of the combined sub-population residing within two standarddeviations of a mean of a measured, sensed, or determined characteristicof the sub-population. As a non-limiting example, a gating region may bedrawn around that portion of a combined sub-population that falls with arange of fluorescence signal intensities centered on the meanfluorescence signal intensity and/or that falls with 2.5 standarddeviations of the scatter signal. Gating regions may be automaticallydefined around sub-populations or sub-groups of cells and may be adaptedin real-time and/or may be updated periodically at regular intervalsand/or when a gating update criteria is triggered.

In general, the predetermined gating selection criteria may be anyselection criteria that assists in satisfying the purity and/or yielddesired for the to-be-sorted population. The gating selection criteriamay be set based on absolute signal values, based on relative signalvalues, based on statistical parameters, etc. for any individuallyidentified sub-populations and/or for any combination of theindividually identified sub-populations. The gating region selectioncriteria may be based on any measured, sensed, and/or determinedcharacteristic(s) as may be reflected on characteristic versus timegraphs, single variable histograms, bivariate plots, set thresholds(absolute and/or relative), statistical analyses thereof, and the like,and/or any combination thereof.

The actual gating region may be determined using any suitablemathematical algorithm. Thus, for example, the gating region may be aregular or irregular polygon, i.e., a region defined by a plurality ofstraight-line segments. Optionally, one or more segments of theperimeter of the gating region may be defined by a multi-ordered curvefit program. For example, where the to-be-sorted sub-populationgenerally forms a circular or elliptical cluster based on thepredetermined characteristics, a circular or elliptical gating regionmay be defined around the cluster. When the population to-be-gated isexpected to assume a characteristic or signature shape, a predeterminedgating shape may be applied. This predefined boundary shape may belocated with respect to a center of mass of the particle sub-populationand/or may be sized to encompass a predetermined percentage of thesub-population. Optionally, a portion or segment of the gating region'sboundary may be provided as a segment having a predetermined shape ordefined by a predetermined mathematical algorithm. A second-order curvemay provide sufficient definition.

According to another aspect, gating regions may be defined around morethan one cell sub-population. Thus, in certain embodiments, a firstgating region may be defined around a cluster of cells that are to besent to a first reservoir (e.g., a sort or keep chamber) and a secondgating region may be defined around a cluster of cell that are to besent to second reservoir (e.g., a waste chamber). In other embodiments,a first gating region may be defined around a cluster of cells to besubjected to a primary sorting operation, a second gating region may bedefined around a cluster of cells that are to be subjected to asecondary sorting operation, and a third gating region or the absence ofa gating region may be defined around a cluster of cells that are toremain unsorted. Alternatively, one or more gating regions may be usedto identify and sort (i.e. reject) a cell population therefore enrichinga cell population for those cells or particles that were not gated.

Each of these cell sub-populations may be independently identifiedaccording to predetermined selection criteria and measured, sensedand/or determined characteristics. Further, each of the cellsub-populations may be independently gated according to predeterminedgating selection criteria. Independently identifying and gating cellsub-populations may provide a means of assuring the quality andconfidence in the cell sub-population of interest. For example,identifying a second gated sub-population may be important if it is aprime concern to ensure that cells from the identified sub-populationare not sorted with the primary gated sub-population (i.e., that theprimary gated sub-population is not contaminated by cells from thesecond gated sub-population).

In some applications involving more than one independently-determinedgating region, the gating regions may be substantially isolated from oneother. However, in other applications, the independently-determinedgating regions may lie adjacent one another and may even overlap. Thus,according to one aspect, when two clusters or gating regions of cellsub-populations (e.g., desired and undesired) have potential significantoverlap, automatically determining a gating region for the desired cellsub-population may include defining a buffer zone between the twoclusters.

In one example embodiment, one or both of the gating regions may bedecreased until there is no overlap. Optionally, one or both of thegating regions may be decreased until there is a buffer zone or gapbetween the gating regions. The overall shape of the gating region maybe maintained even as the size of the gating region decreases.Optionally, the adjacent side(s) of one or both of the adjacent gatingregions may be pulled inward (i.e., away from the other gating region),while the remaining boundary portions of the gating regions remainstationary. In general, if maintaining the purity of the desired orprimary gating region is important, then altering (i.e. increasing ordecreasing) the primary gating region may be advantageous.

In another example embodiment, a common boundary between the twoadjacent or overlapping gating regions may be determined. This commonboundary may be provided as a line located equidistant from a center ofmass of each of the cell sub-populations, as a line equidistance fromtwo predetermined points on a plot of the cell sub-populations, as apredetermined shape or a predetermined mathematical algorithm, as asegment that is coincident with one of the boundary segments of one ofthe adjacent or overlapping gating regions, and/or as a segmentequidistant between adjacent boundary segments of the two adjacent oroverlapping gating regions, etc. Further, it can be seen that thiscommon boundary may be shifted toward or away from either of the gatingregions. For example, rather than being located equidistant (i.e.,50/50) from the center of mass of each of the cell sub-populations, thecommon boundary may be positioned more toward the center of mass of oneof the sub-populations (e.g., a 60/40 or 70/30 or 80/20 split) than theother.

Additionally, according to certain embodiments, the commonly-definedboundary between the adjacent gating regions may be used to furtherisolate the gating regions. The common boundary may be split into twoboundaries (each having the same shape of the common boundary) and movedapart (in parallel or along some other desired geometry) to create abuffer zone or gap between the two adjacent gating regions. This bufferzone or gap may extend over any percent of the distance between thecenters of mass of each the gated cell sub-populations. For example, ifthe buffer zone is centered between the two gating regions, thepercentage distances (from the center of mass to the first gatingboundary/across the buffer zone/from the second gating boundary to thecenter of mass) may range from 50/0/50 to 45/10/45 to 40/20/40 to35/30/35, etc. Further, as discussed with respect to the common boundaryabove, the buffer zone may be shifted toward or away from the primarygating region. Thus, by way of non-limiting example, the percentagedistances may be split 30/30/40, 40/30/30, 50/20/30, 60/10/40, etc.

Operators are familiar with using histograms to confirm that the gatedcell sub-populations are sufficiently distinct and/or isolated. Whencell sub-populations are substantially isolated from one other, ahistogram plot of the cells taken along an axis of the bivariate plotwill display a so called high ‘valley-to-peak’ ratio. The more isolatedthe cell sub-populations, the deeper and wider the valley between cellpopulations. However, in some applications, the gating regions may lieadjacent one another and may even overlap (i.e., occupy a common portionof the characterizing landscape). In such cases a histogram plot of thecells taken along an axis of the bivariate plot may display a low valleyto peak ratio and even, in some instances, may fail to clearly displayany valley. A failure of such a histogram to display distinct peaks (orfailure to display a sufficiently high valley to peak ratio) may be dueto an actual overlap of the gating regions and/or may be due to thegated regions extending over the same data range charted by thehistogram even though occupying distinct portions of the bivariate plot.

According to certain aspects, a histogram may be developed using thecommon boundary described above and plotting the normal distances of thecells from the common boundary. This may provide a visual verificationthat the gating region is properly defined.

According to even further aspects, automatically determining a cellsub-population and/or gating regions may be based on one, two, three,four, . . . “n”-dimensional cell data.

Exemplary Monitoring and/or Tracking of Particle Populations:

In exemplary embodiments, system 100 (e.g., via sensors 116 andprocessor 114) may be configured and adapted to track a cell populationor populations for operatorless operation, and/or for sorting particlesto account for varying operating conditions of system 100 (e.g.,instruments and/or instrument component variations, varying environmentaround system 100, and/or variations between samples, as non-limitingexamples). In general, particle populations (e.g., a grouping of cellsthat are considered similar), and/or cluster positions based on certaindata representations, may be monitored, and the data and/or sort gateand/or region conditions or boundaries may then be adjusted (or“tracked”) to account for minor fluctuations in measured signal levelsso that sorting (particle processing) may continue with minimal impacton sort purity and recovery.

For example, in one exemplary system 100 region tracking algorithm, thealgorithm adjusts the position of the active sort region (e.g., a sortgate) with respect to a particle population, as displayed on a bivariatedata plot, in response to data from a Field Programmable Gate Array(“FPGA”) or other suitable processor containing particle eventinformation (e.g., light pulse characteristics that may include pulseheight, width, area or other characteristics).

According to certain aspects, once a region is defined (whether by humanor by machine/operatorless technique as described above) around some orall of a particle sub-population, the centroid of a tracked region maybe calculated. A tracked region may apply to a population orsubpopulation of cells or particles to designate, track and/or monitorcells or particles, and may also be used for sorting purposes. Asparticles are processed, the center of mass for particle events in a setof current data packets (e.g., a specified amount of data for one ormore particle events) from the processor may then be calculated. Thespecified number of particle events for each data packet may be preset.Further, the number of data packets included in a set may be adjusted tomake the tracking more or less responsive. Next, the difference betweenthe region's centroid and the particle events center of mass may becalculated.

In an exemplary embodiment, the following steps may then be performed bysystem 100: (i) the current centroid of the tracked region iscalculated; (ii) for each new set of data packets from the processor,the current center of mass of the new or cumulative data is calculated;(iii) the difference between the current centroid of the tracked regionand the current center of mass of the data is calculated; (iv) if thedifference is above a defined threshold, this may indicate a so-called“sample boost” operation or some other unusual event of the sorter, andmay not require moving the gating region; (v) if the difference is belowa defined threshold, the gating region's position is adjusted by thedifference; (vi) steps i through v are repeated. These steps may beperformed in real-time, effectively tracking the data location andtherefore particle or cell population.

With respect to step (ii) above, the center of mass may be calculatedfor the new set of data packets only, or the center of mass may becalculated for the cumulative particle data, and/or the center of massmay be calculated for certain subsets of the new data and/or the earlieracquired particle data. For example, the center of mass may becalculated based on the newly acquired data packet and a predeterminednumber of previously acquired data packets. The size of the data packetsmay be associated with the event rate. For example, a high event ratemay limit the data packet to that data collected over only a few secondsof processing.

Optionally, other thresholds may be considered. For example, if thedifference is below a lower threshold, the position of the sort regionmay be considered within the target zone and no adjustment may be made.Further, if the difference is above the upper threshold for apredetermined number of queries at step (iv), the gating region may beadjusted by the difference.

Further, the gating region may be tracked and/or adjusted using datumother than a centroid of the gating region and the center or mass of thedata packets. By way of non-limiting example, if the height, width,shape, density, etc. of the population changes, the region may beexpanded, contracted, reshaped, etc. to ensure inclusion of relevantevents in the region.

Exemplary Droplet Break-Off and/or Droplet Neck Thickness Monitoring:

The droplet break-off of droplets in particle processing systems mightfluctuate for various reasons (e.g., temperature or sample effects)affecting the purity, thus requiring periodic attention by a humanoperator. Moreover, maintaining steady operation of conventionalparticle processing systems is a tedious task, and exceptions duringoperation of such systems might go unnoticed for some time.

Thus, according to even other aspects, system 100 (e.g., via imagingassembly 102 or the like) may be configured and adapted to monitor thedroplet 138′ break-off image and automatically adjust the amplitude andphase controls of the droplet generator to maintain the position and/orprofile at the neck of the last attached droplet 138′.

In certain embodiments, system 100 is configured to maintain steadybreak-off point and neck thickness of droplet 138′ via the adjustment ofthe Drop Drive Amplitude (“DDA”) and the Drop Drive Phase (“DDP”).System 100 may also calculate and set-up the drop delay.

In exemplary embodiments of the present disclosure, system 100 assists auser by providing a real-time measurement, monitoring and adjustment ofthe break-off point and neck thickness of droplet 138′. The dropletbreak-off point and the droplet neck thickness may be controlled viareal-time and or on-demand operatorless adjustment of the Drop DriveAmplitude (“DDA”) and the Drop Drive Phase (“DDP”) parameters.

A high speed camera may take pictures of droplet stream, including thedroplet break-off point and/or the droplet neck region, as rapidly asbetween every microsecond and every 50 microseconds. The high speedcamera may operate in phase or out of phase with the droplet formationsignal or with a particular phase offset. Features extracted from thecamera images of the fluid stream may include: edge detection, fluidstream features (e.g., thicknesses, wavelengths, droplet shape andposition, neck geometry and position, aspect ratio, contrast,statistical characteristics such as means and standard deviation anyparameter, etc. Further, images may be acquired at a lower frequency,but mimicking high speed acquisition through rapid lighting sequences ina synchronous or asynchronous fashion with droplet formation dynamics.

As a non-limiting example, the following steps may then be performed bysystem 100 in an operatorless fashion: (i) driving a stream with adroplet generator at a predetermined input oscillation frequency,amplitude and phase to form droplets; (ii) generating images of thedroplet stream in the vicinity of a predetermined droplet breakoffpoint—these images are synchronized with the frequency of the dropletgenerator; (iii) comparing sequential images of the stream (i.e.,compare sequential pixel counts associated with the stream width at afixed z-axis location (i.e., along the length of the stream) todetermine if the sequential pixel counts are changing or remainingsubstantially the same; (iv) stabilizing the images of the stream, ifnecessary, by adjusting the frequency of the image generator until pixelcounts associated with the fixed z-axis location are substantiallyconstant; (v) determining a z-axis “zero” location where the width ofthe stream first goes to zero (i.e., where the pixel count of the imageof the width of the stream is zero); (vi) repeating step (v) andcalculating a “zero” location difference between the sequentiallydetermined z-axis “zero” locations; (vii) adjusting the DDP to reduce oreliminate the “zero” location difference; (viii) determining a “neck”width where the width of the stream first achieves a local minimum abovethe z-axis “zero” location by comparing stream width pixel counts atadjacent z-axis stations; (ix) repeating step (viii) and calculating a“neck” width difference between the sequentially determined “neck”widths; (x) adjusting the DDA to reduce or eliminate the “neck” widthdifference; and (xi) repeating steps (iii) to (x). With respect to step(v), the width of the stream goes to zero right below the last attacheddroplet 138′. With respect to step (vi), the local minimum immediatelyabove the z-axis “zero” location corresponds to the droplet breakoffpoint. These steps may be performed in real-time, effectivelymaintaining the fluid stream in a constant configuration and eliminatingfluctuations or variability in the droplet formation without requiringoperator intervention. Other algorithms, including variations of theabove-disclosed algorithm, may be used to maintain the droplet breakoffpoint at a fixed station.

FIG. 5 depicts a screenshot from an exemplary droplet break-off monitorassociated with system 100. In exemplary embodiments, the operatorlessmonitoring of the droplet break-off and/or neck thickness of system 100allows the break-off point and/or neck thickness targets of droplet 138′to be set, and automatically adjusts the DDA and/or the DDP whenrequired. Exemplary droplet break-off monitoring of system 100 mayinclude spreadsheet ready files, and may include plotting neck thicknessversus time and/or break-off point versus time. FIG. 5 shows a zoomed-inview of the jet and neck thickness at the last attached droplet 138′.

Exemplary Drop Delay Monitoring:

In particle processing systems, the time between detection of a particle(or cell) in a detection zone and charging of a droplet containing thatdetected particle (i.e., the drop delay) might fluctuate for variousreasons (e.g., temperature, pressure, sample characteristics, etc.),thus requiring periodic attention by a human operator. Thus, accordingto even other aspects, system 100 (e.g., via imaging assembly 102 or thelike) may be configured and adapted to automatically monitor and/orcalculate the drop delay. Based on the operatorless real-timedetermination of drop delay, a charge may be applied to the lastattached droplet 138′.

In certain embodiment of a particle processing system 100, a fluidstream may be perturbed into droplets by an oscillator (i.e., a dropletgenerator) as the stream exits an orifice. Typically, after exiting thenozzle or orifice, the fluid stream exhibits increasingly pronouncedundulations and/or decreasing neck thicknesses in a downstream directionuntil a break-off point is reached where droplets break away from thefluid stream. The break-off point is defined as the last point at whicha droplet contacts the fluid stream, and thus, this location representsthe last point in time a charge may be applied to a droplet to effect anet retention of charge on a droplet for subsequent electrostaticdeflection. The appropriate time to apply this charge is known as thedrop delay. Typically, the drop delay is calculated or determined fromthe time at which a particle is detected. As droplets may be formed at arate of between about 20,000 per second and 200,000 per second, the dropdelay must be very precisely calculated. After the application of changeand break-off, the droplets may pass through an electromagnetic fieldproduced by deflection plates. Thus, the charge applied to each dropletdetermines which path the droplet will follow and which collectioncontainer or other location and/or object it will fall into or on.

In exemplary embodiments, system 100 is configured to automaticallycalculate and set-up the drop delay based on a real-time measured streamfluctuation. In other word, droplets may be charged based on (i) a timeof particle detection in the detection zone; (ii) a distance between theparticle detection zone and the droplet break-off location; and (iii)the real-time measurement and determination of the time for the streamto traverse this detection-zone to break-off distance.

As a non-limiting example, the following steps may be performed bysystem 100 in an operatorless fashion: (i) driving a stream with adroplet generator at a predetermined input oscillation frequency,amplitude and phase to form droplets; (ii) generating at least one imageof the droplet stream so as to encompass at least one undulation betweenthe detection zone and the break-off point; (iii) determining acharacteristic undulation length of the stream (e.g., determine pixelcounts associated with a distance between adjacent local minimums (i.e.,necks) of the undulating stream and/or determine pixel counts associatedwith a distance between adjacent local maximums (i.e., droplet maximumdiameters) of the undulating stream); (iv) calculating a characteristicspeed of the stream based on the determined characteristic undulationlength and an characteristic oscillation frequency associated with thedroplet generator; (iv) calculating time for the stream to travel fromthe detection zone to the break-off point based on the determinedinstantaneous speed of the stream and a determined distance between thedetection zone and the break-off point. The determined distance betweenthe detection zone and the break-off point may be: provided as an input;determined based on stream characteristics and measured oscillationfrequency and/or phase; determined based on instantaneous real-timecalculation of the stream's “zero” location and/or “neck” location, aspresented above; etc.

According to some embodiments, the multiple images may be taken and each(or select) images may be used to determine an instantaneous undulationlength of the stream. The instantaneous undulation length in conjunctionwith an instantaneous oscillation frequency associated with the dropletgenerator may be used to calculate an instantaneous speed of the stream.The delta time between the examined images in conjunction with thecalculated instantaneous speed of the stream may be used to determine adelta distance traveled by the stream between images. The drop delay maybe calculated by dividing the distance between the detection zone andthe break-off point by the delta distance (i.e., the distance traveledbetween images) and then multiplying the delta time (i.e., the timebetween images) by this ratio. Optionally, a series of multiple imagesmay be examined, and multiple delta times and associated delta distancesmay be repeatedly determined to account for variations in the speed ofthe stream during a drop delay time span. A high resolution imagingelement may be used conjunction with high speed data acquisition andprocessing (e.g., using a field programmable gate array) in order totake multiple images of the stream and to determine the precisedistances traveled between image capture. The drop delay may beinstantaneously determined on a droplet-by-droplet basis. Otheralgorithms, including variations of the above-disclosed algorithms, maybe used to determine drop delay without requiring operator intervention.

First Exemplary Alignment Algorithm:

In exemplary embodiments, the alignment of system 100 (e.g., via sensors116 and processor 114) may be accomplished in the presence or absence ofparticles. In general, the optical measurement devices of system 100 maybe adjusted (e.g., via sensors 116 and processor 114) by positioningvarious mechanical and/or optical components, or by effecting thedirection or position of one or more optical paths or particle paths toenable reliable and consistent measurement and/or sorting of particlesflowing within system 100.

Basic alignment of the excitation energy source 152, the detectors, andoptical components in the excitation beam path, and optical componentsin the collection beam path may be performed during assembly of thesystem 100. These alignment positions may be locked in or may be used asnominal positions for any further adjustment using translational and/orrotational stages.

For example, the position of excitation energy source 152 may be alteredat the measurement point (e.g., by altering the position of source 152and/or mirrors or lenses associated with source 152). The position ofnozzle 132 and/or particle inspection region 122 may also be altered.Additionally the position of detectors of detector assembly 156 may bealtered (one or more of these detectors may be fixed and others may movearound such fixed components).

An automated alignment of a stream (with or without samples, targetparticles, calibration beads, etc.) may then be performed. This streamalignment may utilize translational and/or rotational positioning of thestream so that the intersection of the stream with the optical pathextending from the excitation energy source 152 to the detectorassemblies is optimized. In a preferred embodiment, the stream-formingelement, e.g., nozzle 132 may be moved along three translational axes.Additional adjustment degrees of freedom may be utilized if desired.

For example, the positions of these components may be altered based uponan open loop that uses machine vision or the like, and/or based upon aclosed loop that may use feedback from signal signature, e.g.,image-based alignment of nozzle 132 and/or excitation source 152 to apre-defined position where an image is adjusted with respect to expectedconditions at which point a user may take control to fine-tune system100 if desired, and/or data-based alignment of nozzle 132, excitationsource 152 and/or detector positions using feedback from measuredphotodetector signal (e.g., from calibration or target particles).

Finally, according to certain embodiments, in a fine-tuning alignmentprocedure, using feedback from a photodetector signal based onillumination of the sample, particles, beads etc. with the excitationenergy source 152, one or more components of a signal collection and/ortransmission path(s) for a sample's emitted signal (e.g., usingcalibration or target cells/particles) may be physically adjusted tooptimize the signals received by the photodetector. For example, acalibration sample may be run and one or more components along thecollection and transmission paths may be physically tweaked orfine-tuned to optimize the reception of the various signals (scatter,fluorescence, etc.) by the detector assemblies. Motorized adjustmentstages (translational and/or angular axes) may be controlled based onsignals received by the detector assemblies and analyzed by theelectronics.

As a non-limiting example, the scatter signal may be fine-tuned so thata scatter histogram would show distinct peaks and valleys and/or thepeak-to-valley ratio would be maximized. Such physical fine-tuning ofthe collection/transmission path typically may be accomplished bytranslating and/or rotating optical elements within thecollection/transmission path. For example, the detector assembly may bemoved laterally (side-to-side and/or up and down) to the beam path so asto ensure that the signal intensity is maximized.

These stream alignment and/or full alignment sequences may be executedeach time a particle analysis and/or sorting process is performed.Alternatively, a conditional and/or adaptive alignment algorithm may beprovided. As an example embodiment, parameters of previous runs may becompared to threshold parameters to determine if an alignment sequenceshould be performed. Parameters may include environmental conditions(e.g., temperature, humidity, pressure, etc., and changes thereof);operational conditions (e.g., time between runs, number of runs sincelast alignment, machine updates (software, firmware and/or hardware),user experience, user identification, etc., and changes thereof); sampleconditions (e.g., sample batch or lot, sample protocols, sample age,sample uniqueness, etc., and changes thereof); run conditions (e.g.,desired purity, yield, flow rate, sort rate, etc., and changes thereof);and anomalies in past runs (e.g., clogs, unexpected data, etc.).Comparing certain predetermined parameters to predetermined fine-tuningcriteria and/or thresholds may trigger an instruction to perform afine-tuning alignment procedure or a portion thereof. Comparing the sameor other predetermined parameters to predetermined operational criteriaand/or thresholds may trigger an instruction to perform an operationalalignment procedure or a portion thereof, followed by a fine-tuningalignment procedure or portion thereof. Thus, depending upon the extentto which conditions have been altered or have not been altered, theremay be no need to perform any alignment sequence. Such a conditionaland/or adaptive alignment algorithm may reduce the amount of time astable processing system spends in alignment mode.

Second Exemplary Alignment Algorithm:

According to certain aspects, system 100 may be fully aligned withoutrequiring a sample (or other calibration particles) to flow through thedetection region. In other words, system 100 may be aligned withoutusing feedback from a photodetector receiving an emitted signal from aset of excited calibration or target particles. This may be referred toas a streamlined or reduced alignment algorithm.

In a non-streamlined or full alignment procedure, using feedback from aphotodetector signal, the components of a signal collection and/ortransmission path(s) for a sample's emitted signal (e.g., usingcalibration or target cells/particles) may be physically adjusted tooptimize the signals received by the photodetector. For example, in thepast, a calibration sample may have been run and the collection andtransmission paths may have been physically tweaked or fine-tuned tooptimize the reception of the various signals (scatter, fluorescence,etc.) by the detector assemblies. Thus, additional adjustment stages(translational and/or angular axes) would have been necessary tomove/adjust one or more of the optical elements in the emitted signalcollection/transmission path. As a non-limiting example, the scattersignal may have been fine-tuned so that a scatter histogram would showdistinct peaks and valleys and/or the valley to peak ratio would bemaximized. Such physical fine-tuning of the collection/transmission pathtypically requires several additional stages and would take anywherefrom ten to fifteen minutes, even when automated. This full alignmentsequence may be executed each time a particle analysis and/or sortingprocess is performed.

This fine-tuning alignment of system 100 may be eliminated in thestreamlined or reduced alignment algorithm.

In an exemplary embodiment, the physical alignment of system 100 may beaccomplished using only two steps. In a first step, the excitationenergy source 152 may be physically aligned to a detector assembly 156when the system 100 is first assembled. In a second step, the positionof nozzle 132 and/or particle inspection region assembly 122 may also beadjusted with respect to the excitation energy source 152 using threetranslational stages (X, Y and Z). This may be an image-based physicalalignment of nozzle 132, which may be automated as described above.These two alignment steps do not require the presence of detectablesample (e.g., calibration beads, cells, particles, etc.).

Thus, according to certain embodiments, post-assembly alignment of theparticle detection subsystem (i.e., an excitation energy source 152, anexcitation energy source optical assembly, a detector assembly 156, asignal collection optical assembly (or assemblies), and the nozzle 132)may be accomplished with only three relative translations. Duringassembly, the excitation energy source 152, the excitation energy sourceoptical assembly, the detector assembly 156, and the signal collectionoptical assembly may be aligned and then locked down. Post-assembly andprior to processing a sample (or calibration beads), the nozzle 132 maybe moved in the X, Y and/or Z directions in order to aligned the samplestream in the path of the excitation beam. No further physical movementor adjustment of the elements or components comprising the particledetection subsystem needs to be performed.

Thus, advantageously, the components comprising the excitation energysource 152, the excitation energy source optical assembly, the detectorassembly 156, and the signal collection optical assembly do not requireadjustable mounting stages.

Optionally, even if adjustable mounting stages are provided for one ormore of the components comprising the excitation energy source 152, theexcitation energy source optical assembly, the detector assembly 156,and the signal collection optical assembly, an alignment algorithminvolving these adjustable mounting stages need not be invoked after thesample stream is located within the excitation beam and/or prior toevery particle processing run.

According to certain embodiments, a data-based signal manipulation maybe used to fine-tune the data collection, thus eliminating the need tophysically adjust the collection and/or transmission paths of a sample'semitted signal (e.g., using calibration or target cells/particles) tooptimize the signals received by the photodetector. In other words, thesample's emitted signal (e.g., side scatter, fluorescence, etc.) in apotentially less-than-optimal condition may be received by the detectorassembly 156 and automatically analyzed to identify targetsub-populations, identify non-target sub-populations, determine gatingregions and/or conduct sorting operations. As described above withrespect to the determination of particle clusters/sub-populations and/orgating regions, sub-populations of particles or cells emitting less thanoptimal side scatter signals may still be identified and gated withconfidence that the desired cells are being captured with the desiredpurity and yield. Thus, the physical fine-tuning of thecollection/transmission path of the sample's emitted signal may beeliminated.

Example II: Microfluidic Flow Sorter Particle Processing System

Referring now to FIG. 6, there is illustrated a block diagram of anotherexemplary embodiment of a particle processing system 200 according tothe present disclosure. Similar to systems 10 and 100, particleprocessing system 200 is configured, dimensioned and adapted foranalyzing, sorting, and/or processing (e.g., purifying, measuring,isolating, detecting, monitoring and/or enriching) particles (e.g.,cells, microscopic particles, etc.) or the like, and wherein humanintervention is not required and/or is minimized.

For example, system 200 may be a cytometer and/or a cell purificationsystem or the like, although the present disclosure is not limitedthereto. In exemplary embodiments, system 200 is a microfluidic flowsorter particle processing system 200 (e.g., microfluidic chip basedsystem) or the like. Exemplary microfluidic flow sorter particleprocessing systems/components or the like are disclosed, for example, inU.S. Pat. Nos. 8,277,764; 8,123,044; 7,569,788; 7,492,522 and 6,808,075;U.S. Patent Publication Nos. 2012/0009025; 2012/0277902; 2011/0196637and 2009/0116005; and U.S. Patent Application Ser. Nos. 61/647,821 and61/702,114, the foregoing being incorporated herein by reference intheir entireties.

Similar to systems 10 and 100 and as shown in FIG. 6, system 200includes at least one processor 214 (e.g., a central automationprocessor or master processor). At least one display device 212 is incommunication with processor 214. Processor 214 may also be incommunication with (e.g., one or a plurality of) keypads and/or userstations 211, third-party devices 213 and/or additional processorsand/or controllers 215. Processor 214 is generally capable ofcommunication with a network or internet 217, and capable of sendingand/or receiving audio, video and/or data or the like.

System 200 includes a microfluidic assembly 218, the microfluidicassembly 218 in communication with a particle inspection region assembly222. System 200 also includes an electromagnetic radiation or lightsource assembly 220, a particle collection assembly 224 and an opticaldetector assembly 226. Processor 214 is in communication withmicrofluidic assembly 218, electromagnetic radiation source assembly220, particle inspection region assembly 222, particle collectionassembly 224 and/or an optical detector assembly 226.

Similar to systems 10 and 100, particle processing system 200 includesat least one sensor assembly/member 216 that is configured and adaptedto sense or monitor at least one operational characteristic orprocessing feature of system 200 (e.g., sense at least onecharacteristic of microfluidic assembly 218, electromagnetic radiationsource assembly 220, particle inspection region assembly 222, particlecollection assembly 224 and/or an optical detector assembly 226). Eachsensor assembly 216 is in electrical communication with processor 214,and system 200 may include a plurality of sensor assemblies 216 a-“n”.

It is to be noted that system 200 may include a plurality of assemblies218, 220, 222, 224 and/or 226, and/or a plurality of processors 214 andsensors 216. Further, microfluidic assembly may include a plurality ofmicrofluidic channels.

In general, processor 214 is configured to change (e.g., automaticallychange) one or more parameters, features, characteristics and/orcomponents of system 200 based on the one or more operationalcharacteristics sensed by the one or more sensor members 216. As such,processor 214 is generally configured and adapted to enable orfacilitate system 200 to process particles in an operatorless fashion.

Processor 214 is generally configured to transmit and/or receive signals(e.g., command and/or status signals) or the like to and/or from sensorassemblies 216 and/or microfluidic assembly 218, electromagneticradiation source assembly 220, particle inspection region assembly 222,particle collection assembly 224 and/or an optical detector assembly226, in order to change the status and/or operating parameters ofmicrofluidic assembly 218, electromagnetic radiation source assembly220, particle inspection region assembly 222, particle collectionassembly 224 and/or an optical detector assembly 226. Stated anotherway, processor 214 is in communication with sensors 216 and/or thecomponents of system 200 for control and/or communication purposes.

For example, processor 214 may send command signals to a sensor assembly216 associated with microfluidic assembly 218 (and/or directly tomicrofluidic assembly 218) to control or change the status or operatingparameter of microfluidic assembly 218. Moreover, processor 214 mayreceive status signals from sensor assemblies 216 regarding the statusof the components of system 200.

Each sensor assembly 216 may include or be associated with a localprocessor and/or processing unit (e.g., signal processing and/or controlunit) or the like. As such, each sensor assembly 216 may be incommunication with at least one component (e.g., assembly 218) of system200 for control and/or communication purposes (e.g., independent ofand/or in conjunction with processor 214). For example, the processor orprocessing control unit local to and/or associated with each sensorassembly 216 may send command signals directly to a component (e.g.,assembly 218) of system 200 to control or change the status or operatingparameter of that component.

Such command signals may or may not be directed from processor 214, andcan be communicated to and/or from processor 214, although the presentdisclosure is not limited thereto. In exemplary embodiments, eachassembly 218, 220, 222, 224 and/or 226 can include a processor or thelike that can operate independent of and/or in conjunction withprocessor 214 for control and/or communication purposes associated withthe components of system 200.

In general, processor 214 and/or sensors 216 are configured to enablesystem 200 to process particles in an operatorless fashion based on theoperational characteristics sensed by the sensor assemblies 216. System200 may have any number of sensor assemblies 216 in communication withprocessor 214.

Turning now to FIG. 7, an example of a microfluidic flow sorter particleprocessing system 200 or the like is illustrated, although the presentdisclosure is not limited thereto. Rather, it is noted that the systemsand methods described may be applied to other particle processingsystems.

FIG. 7 illustrates a system 200 suitable for implementing anillustrative embodiment of the present disclosure. As shown in FIGS.7-8, system 200 includes a microfluidic assembly 218 (e.g., microfluidicchip). Assembly 218 includes a plurality of channels 203 for conveying asubstance, such as particles or cells, therethrough. As discussed below,microfluidic assembly 218 includes and/or is communication with aparticle inspection region assembly 222 and a particle sample fluidinput region 223.

As shown in FIG. 8, microfluidic assembly 218 generally includes asubstrate 201 having a plurality of channels 203 (e.g., microchannels)disposed therein. The channels transport fluid and/or particles throughthe assembly 218 for processing, handling, and/or performing anysuitable operation (e.g., on a liquid sample). Assembly 218 may includeany suitable number of microchannels 203 for transporting fluids throughassembly 218.

In exemplary embodiments, an optical detector assembly 226 (FIG. 7) foruse with microfluidic assembly 218 is provided. At least a portion ofoptical detector assembly 226 may be implemented in particle inspectionregion assembly 222 to interrogate the particles in this region. Atleast a portion of optical detector assembly 226 may monitor flowthrough a plurality of channels 203 simultaneously. In exemplaryembodiments, assembly 226 can inspect individual particles for one ormore particular characteristics, such as size, form, fluorescence,optical scattering, as well as other characteristics. It is noted thatassembly 226 is not limited for use in particle or cell sorting systemsand may be implemented in any suitable system having a substance, suchas particles, to be monitored flowing through one or more channels.

FIG. 7 illustrates an overview of an optical detection assembly 226,which may be implemented for use with microfluidic assembly 218.However, assembly 226 may be implemented in any suitable system and isnot limited for use with microfluidic assembly 218.

System 200 also includes electromagnetic radiation source assembly 220.In certain embodiments, electromagnetic radiation source assembly 220includes one or more electromagnetic radiation or light sources 221(e.g., a laser source(s) or the like) coupled to and/or in communicationwith beam shaping optics 225 (e.g., segmented mirror/mirrors or thelike, flat top elements, and/or other optical elements) for producingand forming one or more beams of electromagnetic radiation (e.g., light)227 that pass through an optical mask 229 (FIG. 9), illustrated as anarray of pinholes 229 a, 229 b (FIG. 9) aligned with an array ofparticle conveying channels 203 in the microfluidic chip assembly 218.

The electromagnetic radiation 227 admitted by the pinholes subsequentlypasses through the conveying channels 203 themselves. The portion ofelectromagnetic radiation beam 227 admitted to each channel 203 via oneor more associated pin holes intersects particles that are conveyedthrough the channel 203 to create optical signals. Examples of opticalsignals that can be produced in optical particle analysis, cytometryand/or sorting when a beam 227 intersects a particle include, withoutlimitation, optical extinction, angle dependent optical scatter andfluorescence. Optical extinction refers to the amount of electromagneticradiation or light that a particle extinguishes, absorbs, or blocks.Angle dependent optical scatter refers to the fraction ofelectromagnetic radiation that is scattered or bent at each angle awayfrom or toward the incident electromagnetic radiation beam. Fluorescentelectromagnetic radiation is electromagnetic radiation that is absorbedby molecules in the particle and re-emitted at a longer wavelength.

In exemplary embodiments, detector optics including, for example, anoptical extinction detection subsystem 231, optical scatter detectionsubsystem 233, and fluorescence detection subsystem 235 of opticaldetector assembly 226, which in some embodiments are located on anopposite side of the channels 203 from the electromagnetic radiationsource assembly 220, capture and observe the optical signals generatedby the intersection of an electromagnetic radiation beam with a particlein a channel 203. In certain embodiments, optical extinction detectionsubsystem 231 are placed directly opposite the electromagnetic radiationsource 221 and aligned with the incident electromagnetic radiation path227 for detecting optical extinction. Optical scatter detectionsubsystem 233 may be placed substantially perpendicular to the incidentelectromagnetic radiation path 227 in the plane formed by the incidentlight vector and the microfluidic channel it intersects. Alternatively,optical scatter detection subsystem 233 may be placed substantiallyperpendicular to the microfluidic chip substrate. A fluorescencedetection subsystem 235 captures optical signals from particlefluorescence. The fluorescence detection subsystem 235 may include alarge high numerical aperture lens 239 and/or other accompanying opticalelements. As shown, the fluorescence detection subsystem 235 is placedabove the microfluidic chip 218 to capture as many fluorescent photonsas possible and image them onto detector 235. A fiber array 236 extendsfrom the image plane and conveys signals to detector 235 for analyzingthe signal. The detectors 231, 233, 235 may be photomultiplier tubes,photodiodes, avalanche photodiodes, a camera(s) or other suitabledevices.

Electromagnetic radiation source assembly 220 and optical detectorassembly 226 are implemented in an interrogation area or particleinspection region assembly 222 of the chip 218. In general, any suitablenumber of channels 203 may be observed using system 200.

FIG. 9 shows an illustrative picture of the cross section through aportion of a microfluidic chip 218 containing a pair of microchannels203 a and 203 b. The cross-section is in a plane that cuts through themicrochannels and the pinholes 229 a, 229 b of the mask 229. Theincident electromagnetic radiation 227 is partly blocked by the pinholelayer 229 and narrows the initial beam 227 to focused beams defined byeach pinhole 229 a, 229 b. The focused beams intersect each channel toilluminate the region in which particles are permitted to flow in a coreflow.

According to some embodiments, stray electromagnetic radiation may beblocked by the pinhole layer 229, which may be a separate part from themicrofluidic chip 218 or may be fabricated on the surface of the chip218 by suitable methods (e.g., photolithography).

As noted above and as shown in FIGS. 6-9, particle processing system 200includes at least one sensor assembly/member 216 that is configured andadapted to sense or monitor at least one operational characteristic orprocessing feature of system 200 (e.g., sense at least onecharacteristic of microfluidic assembly 218, electromagnetic radiationsource assembly 220, particle inspection region assembly 222, particlecollection assembly 224 and/or optical detector assembly 226). As shownin FIGS. 6-9, exemplary system 200 includes a plurality of sensorassemblies 216 a-“n”.

In certain embodiments and as shown in FIG. 6, system 200 includes afirst sensor assembly 216 a that is configured and adapted to sense ormonitor at least one operational characteristic or processing feature ofthe microfluidic assembly 218, a second sensor assembly 216 b that isconfigured and adapted to sense or monitor at least one operationalcharacteristic or processing feature of the electromagnetic radiationsource assembly 220, a third sensor assembly 216 c that is configuredand adapted to sense or monitor at least one operational characteristicor processing feature of the particle inspection region assembly 222, afourth sensor assembly 216 d that is configured and adapted to sense ormonitor at least one operational characteristic or processing feature ofthe particle collection assembly 224, and a fifth sensor assembly 216 ethat is configured and adapted to sense or monitor at least oneoperational characteristic or processing feature of the optical detectorassembly 226. System 200 may have any number of sensor assemblies 216a-“n” in communication with processor 214.

Exemplary processor 214 is programmed and/or configured to transmitand/or receive signals (e.g., command and/or status signals) or the liketo and/or from sensor assemblies 216 and/or microfluidic assembly 218,electromagnetic radiation source assembly 220, particle inspectionregion assembly 222, particle collection assembly 224 and/or opticaldetector assembly 226, in order to change the status and/or operatingparameters of the components of system 200. As such, processor 214generally is in communication with sensors 216 and/or the components ofsystem 200 for control and/or communication purposes. Exemplaryprocessor 214 is programmed, configured and/or adapted to enable orfacilitate system 200 to process particles in an operatorless fashionbased on the operational characteristics sensed by the sensor assemblies216.

Sensor assembly or assemblies 216 a associated with microfluidicassembly 218 may be configured to sense or monitor at least onecharacteristic or feature of sample particle input region 223, channels203, particle inspection region assembly 222 and/or particle collectionassembly 224 so that processor 214 can change one or more parameters orcharacteristics of assembly 218, assembly 222, and/or assembly 224 basedon the sensed or monitored features to enable system 200 to operate inan operatorless fashion.

For example and without limitation, sensor assembly or assemblies 216 aassociated with assembly 218 may sense or monitor such exemplarycharacteristics of sample input region 223, channels 203, particleinspection region assembly 222, particle collection assembly 224, and/orother components of assembly 218 or system 200 including: insertionand/or removal of chip 218, alignment and/or positioning of chip 218,appropriate pressure levels, sample characteristics, sheath fluidcharacteristics, waste status and control, stability, alignmentadjustment issues, flow rates, identifications, durations, appropriatesort control, signal processing, level monitors, volume presence, numberof sorts, purity, yield and/or recovery.

Likewise, sensor assembly 216 b associated with electromagneticradiation source assembly 220 may sense or monitor such exemplarycharacteristics of electromagnetic radiation or light source 221, beamshaping optics 225, and/or other components of assembly 220/system 200including, without limitation: beam shaping/preparation, excitationsource, appropriate power, intensity, beam/light size, wavelength,position, stability and/or motion.

Also, sensor assembly 216 e associated with optical detector assembly226 may sense or monitor such exemplary characteristics of detectoroptics 231, 233, 235 and/or other components of assembly 226 or system200 including, without limitation: alarms, run progress, safety aspects,instrument start-up, adjustment and/or alignment, direction, position,and/or monitor or control functions.

In general, processor 214 is configured to change (e.g., automaticallychange) one or more parameters, features, characteristics and/orcomponents of system 200 based on the one or more operationalcharacteristics sensed by the one or more sensor members 216. As such,processor 214 is generally programmed, configured, and/or adapted toenable or facilitate system 200 to process particles in an operatorlessfashion.

In certain embodiments, other characteristics/aspects of the componentsof system 200 that may be monitored or sensed (e.g., via sensorassemblies 216) and/or operated in an operatorless fashion or manner(e.g., via processor 214 and/or sensors 216) may include, withoutlimitation, the following:

-   (i) instrument start-up (e.g., power sources; electrical sources;    laser sources; excitation sources; fluidics; air/vacuum; pumps;    detection system; processors/computers; sub-systems; safety    mechanisms; self-tests; self-calibration; self-diagnose issues;    self-identification of current state (e.g., readiness) for sorting;    communication of status);-   (ii) input sample (e.g., identification of input sample (what is it    for recording, traceability, acceptance, sequenced, measurement or    sorting) and/or input sample vessel; presence of sample; quantity of    sample at any given time);-   (iii) insertion of sample (e.g., initial insertion of sample to    system 200 (from or within container); running (flow) of sample;    regulation and/or control of sample flow and/or sample flow rate    dynamically (periodically and/or to a set-point that is defined    automatically or in advance during instrument    set-up/manufacture/calibration); monitoring sample volume or level;    monitoring event rate and altering sample pressure and/or expulsion    rates to achieve a desired set-point for particle event (input)    rate);-   (iv) sort collection (e.g., vessel insertion/removal; adjust    position of vessels (waste, sorted fraction(s)) or of unitary    cartridge; sealing of fluidic and/or other necessary connections    required to enable system 200 operation; identification and/or    selection of particles or particle populations of interest for    measurement and/or sorting);-   (v) sort mode and/or automated adjustment and/or alignment of    operating conditions (e.g., to enable predefined and/or    user-specified purity, efficiency, and/or recovery and/or yield    modes (event rate, gating schemes, sort rate, abort rate, population    resolution, etc.); applying various data manipulation algorithms to    calculate and/or automatically adjust data that may be visualized as    a rotation or other translation function on one or more dimensions    and/or on bivariate data plots to assist with the projection of data    in histogram views; adjustment of parameters to bring particle    population within acceptable signal limits to enable reliable    measurement of particles or to enable certain data to be displayed    visually (sensitivity, gain, position of population(s) and/or    photodetector amplification) using software, firmware and/or    hardware (Example—adjust photodetector voltage and/or gain (until    population is in desired location), optical alignment functions are    then enabled (excitation source and/or associated optical and/or    mechanical elements, flow chamber (particles), detectors) using    particles and/or mimic particles or other optical schemes such as    light sources, image processing methods or machine vision as    non-limiting examples));-   (vi) adjusting a sort mechanism (e.g., side calibration timing    and/or velocity and expected arrival at sort position/mechanism to    enable reliable and stable performance of particle separation to    meet the desired outcome (such as given number of particles, desired    purity, ratio, recovery, yield, characteristic property,    homogeneity, heterogeneity, size, morphology, fluorescence, light    scatter properties, immunophenotypic marker profile, DNA content,    etc.) (Example—determine either directly (e.g., measuring actual    time) or indirectly (e.g., velocity) the time of flight for a    particle to travel from an inspection zone to a processing region,    such as a sort/switch region);-   (vii) adjusting optical measurement apparatus (e.g., through    positioning various mechanical or optical components, or by    effecting the direction or position of one or more optical paths or    particle paths to enable reliable and consistent measurement and/or    sorting of particles flowing within system 200 (e.g., within the    cytometer apparatus); monitor and control functions (e.g., system    leaks (gas or liquid); out of bounds (power, safe shut-down,    instrument safety and control network, universal power supply,    etc.); trending (e.g., sample quality, sort rate, sort fraction,    assessment of live to dead ratio within a sample, scheduling of    samples, alarm conditions and alarms); intelligent error handling    such as self-fixing, self-regulation or other act such as by    reacting to system 200 parameters (e.g., parameter change such as    temperature, pressure, vacuum, alignment movement, etc.) that may    affect system/instrument operation);-   (viii) various alerts and/or alarms (e.g., alerts or alarms that    caution device or user that system is nearing or operating outside    acceptable limits/window; run and control sheath (waste, sample,    sort fraction and trajectory of sort and non-sort fractions) level    monitor and refill; cleaning lines; sample waste; etc.);-   (ix) safety aspects (e.g., safety of environment or from environment    of operator or sample or system/instrument); potential exposure of    sample to the environment, the apparatus, and other samples;-   (x) automated and/or robotic feeding of samples, such as sheath    fluid(s), sort output fractions, waste and other required fluids,    consumables, calibration parts, cleaning supplies, etc. (e.g.,    systems/methods to enable continuous operation over extended periods    (e.g., for different samples) without the need for human    intervention); (xi) remote-controlled features and/or operations    (e.g., reduce requirement for operator to be in front of system 200,    system 200 could be controlled from a remote location or room with    respect to the system 200; remote-controlled features that may be    particularly useful if there are concerns over sample contamination    issues (between samples, or sample and system or environment, or    sample and operator, as non-limiting examples), or concerns where    pathogens, communicable diseases or the like or other human or    non-human vectors are involved (e.g., Hepatitis C, Influenza    strains, Malaria, H1N1, HIV, BSE, TB, etc.));-   (xii) other aspects of system 200 (e.g., laser alignment; excitation    source alignment; detector alignment; data manipulation for    identification and zooming; population identification; population    sort regions; set-point purity; etc.);-   (xiii) auto-rotation (e.g., calculating and automatically adjusting    data rotation on one or more bivariate plots to assist with    projection of data in histogram views and related gating or sort    strategies);-   (xiv) event rate (e.g., monitoring event rate and controlling sample    pressure to achieve a desired set-point for particle event rate);-   (xv) coarse alignment (e.g., image-based alignment of chip and/or    excitation source to predefined position where image is adjusted    with respect to expected conditions); and/or-   (xvi) fine alignment (e.g., data-based alignment of chip, excitation    source and/or detector position using feedback from measured    photodetector signals (e.g., from calibration or target particles;    identify and locate specific sort regions around certain cell    populations, such as cells that have been identified as providing    therapeutic potential, further use in research or industrial    activities, or live oriented X and/or Y sperm cells as non-limiting    examples)).

Moreover, the processors 214 and sensor assemblies 216 of the presentdisclosure may be advantageously utilized to sense or monitor even othercharacteristics of system 200, including, for example, othercharacteristics or aspects disclosed and described in U.S. Pat. Nos.8,277,764; 8,123,044; 7,569,788; 7,492,522 and 6,808,075; U.S. PatentPublication Nos. 2012/0009025; 2012/0277902; 2011/0196637 and2009/0116005; and U. S. Patent Application Ser. Nos. 61/647,821 and61/702,114, each incorporated by reference herein in their entireties.

In exemplary embodiments, the alignment of system 200 (e.g., via sensors216 and processor 214) may be accomplished in the presence or absence ofparticles or cells. In general, the optical measurement devices ofsystem 200 may be adjusted (e.g., via sensors 216 and processor 214) bypositioning various mechanical or optical components, or by effectingthe direction or position of one or more optical paths or particle pathsto enable reliable and consistent measurement and/or sorting ofparticles flowing within system 200. In certain embodiments, system 200is configured and adapted for the operatorless alignment (in thepresence or absence of particles) of one or more microfluidic chips 218(e.g., sorter structures).

In exemplary embodiments, system 200 (e.g., via sensors 216 andprocessor 214) is configured and adapted to pre-align various opticalcomponents of system 200 prior to the insertion of one or moremicrofluidic chips 218 by utilizing optical techniques and/or byutilizing another one or more microfluidic chip or chips 218. In certainembodiments, system 200 is configured to adjust its optical componentsto produce one or more electromagnetic radiation or excitation beams 227that are of a predefined and/or acceptable profile, size, energydensity, divergence and/or convergence, wavelength, spatial and/ortemporal characteristic.

System 200 may also be configured to align the beams 227 with respect toelectromagnetic radiation collection path and/or detectors of opticaldetector assembly 226. For example, such alignment may be determined bysensor 216 types of which include photodetectors (e.g. photodiodes,photomultiplier tubes, multi-element devices such as photomultiplierarrays, linear CCD arrays, cameras and the like).

System 200 may be configured to introduce and/or move microfluidic chip218 into place so that electromagnetic radiation beam 227 is incident onor near a region of interest such as particle interrogation region 222a. System 200 can then adjust the chip 218 and/or optical path positionsin one or more axes (e.g., including one or more of x, y, z, yaw ortheta, pitch, or roll axes), and for the case of a plurality ofmicrofluidic sorters within a single chip 218 on substrate 201, a globaltranslation or rotation in one or more axes. System 200 may furtherfine-tune alignment steps to further adjust particle measurement such asutilizing optical apertures (on- or off-chip 218, or a combination ofboth) to isolate particular regions of excitation and/or lightcollection. For example, it may be desirable to provide a tighterposition of chip 218 by putting optical apertures in place (in additionto masks that may already be in use).

The chip 218, various optical components of system 200, and/or opticalpaths may be modified by the system (e.g., via motion control stages) todetermine or set the location of any parameter of system 200. Forexample, a linear scan may be performed one or more times to sweepthrough multiple locations so that the peak signal (e.g., excitation,fluorescence, scatter, etc.) intensity or power or some other positionmay be found. Moreover, a combination of rotation and/or linear scanactions may also be conducted by system 200 to achieve similar purposes.

Furthermore the shape and/or location of any apertures of chip 218 maybe used as yet further aids for aligning. For example, withoutlimitation, the relative amount (e.g., ratio) of electromagneticradiation transmitted by two or more apertures of chip 218 may bemeasured as the alignment of components within the system 200 ischanged. A peak ratio or the like may be used to identify when anelectromagnetic radiation or excitation source 221 is appropriatelypositioned with respect to a microfluidic sorter 218, and/or a particlemeasurement location 222 a.

Further, optical alignment techniques of system 200 may includealignment by monitoring a plurality of particle measurement locations222 a, and/or a plurality of electromagnetic radiation or lightcollection components or optical paths. In certain embodiments, opticalfibers or optical fiber bundles and/or arrays (e.g., detectors 231) maybe used for electromagnetic radiation collection, and may be movedindividually or collectively to adjust electromagnetic radiationdetection with respect to an electromagnetic radiation source 221 andone or more microfluidic sorters 218.

Such functions may be performed in an automated fashion that usesalgorithms that monitor and/or adjust certain signals and/or positionsof one or more components of system 200. For example, a processor 214 orthe like programmed with software algorithms may be used to determineand/or control optical alignment of system 200. In other embodiments,software algorithms may be implemented in other devices such as, withoutlimitation, microprocessors, field programmable gate arrays, etc. Othersuitable mechanical components and/or movable elements of system 200 maybe utilized to perform required motions in any one or more dimensions.As noted, measurements and/or operatorless optical alignment functionsmay be performed in the presence or absence of particles flowing throughthe one or more microfluidic sorters 218.

Exemplary Microfluidic Alignment:

In exemplary embodiments, system 200 (e.g., via sensors 216 andprocessor 214) is configured and adapted for aligning a plurality ofmicrofluidic sorters within one or more microfluidic chips 218 withoutoperator intervention, by following the below noted steps. For example,processor 214 may control (e.g., programmatically control or perform)the following steps to facilitate operatorless alignments:

1) Processor 214 of system 200 aligns a detector (e.g., the axialelectromagnetic radiation extinction fiber ribbon (linear array)assembly 231) with respect to the electromagnetic radiation 227 fromsegmented mirror 225 (for multiple electromagnetic radiation beams, itis noted that there may be a one to one or other relationship of beamsand/or paths and electromagnetic radiation collection and detectionpaths).

-   -   a. System 200 programmatically sets electromagnetic radiation        221 to low power, to avoid damage to any part of electromagnetic        radiation fiber assembly 231.    -   b. Microfluidic chip 218 is then homed (e.g., returned to a        known reference position or starting position) using, for        example, chip stage y-axis, to remove it from the        electromagnetic radiation path (e.g., no interference). As used        herein “x-axis” and “y-axis” extend in directions within the        plane of the cross-section of the electromagnetic radiation beam        and “z-axis” extends in a direction along the axis of the        electromagnetic radiation beam. As such, the movement or        adjustment of any particular component, if described in terms of        x-axis, y-axis or z-axis stages, is relative to that component's        position in the path of the electromagnetic radiation beam. In        addition the y-axis extends in a direction across (i.e.,        lateral) to the fluidic flow. The x-axis extends in a direction        aligned (i.e., longitudinal) with the fluidic flow.    -   c. System 200 positions the detector assembly (e.g., the        electromagnetic radiation extinction detector) stage x- and        y-axes to nominal (e.g., pre-determined, calibrated, or taught)        positions.    -   d. System 200 aligns the detector assembly (e.g., the extinction        detector) stage x-axis to a desired position for most        electromagnetic radiation by scanning the nominal range (field        of interest which may be equal to or smaller than the full range        of motion of one or more axes), then determining measured        optical power values, and averaging desired positions for all        microfluidic sorter detection channels 203. Two scans may be        used. The first produces a coarse-aligned position by scanning a        nominally wide range with a large step value. From the desired        position from the coarse scan, system 200 then scans a narrow        range about the desired position with small step values. This        produces a fine-aligned position.    -   e. System 200 aligns electromagnetic radiation extinction y-axis        to a desired position for most electromagnetic radiation, (same        scan method as discussed above).        2) System 200 aligns chip 218 with respect to electromagnetic        radiation 227 from segmented minor 225    -   a. System 200 then provides fluid flow through chip 218 (flow        may be provided by sheath only; sample, particles or beads are        not required).    -   b. System 200 moves chip 218 into nominal (e.g., a known,        previous, expected, and/or reference) position in        electromagnetic radiation path.    -   c. System 200 sets laser to high(er) power.    -   d. System 200 jogs (e.g., moves) extinction source in x-axis to        compensate for refraction of electromagnetic radiation (e.g.,        laser light) through chip 218.    -   e. System 200 aligns chip 218 x-axis to desired position for        most electromagnetic radiation (e.g., maximum electromagnetic        radiation transmission through chip 218 microsorter flow        channels 203), by scanning nominal range, recording measured        optical power values, and averaging positions for all flow        channels 203.    -   f. Align chip 218 y-axis to position, same method as above.    -   g. Align chip theta (rotational) axis to position, same method        as above.        3) System 200 re-aligns extinction ribbon 231 x-axis.    -   a. Chip 218 is still flowing fluid (e.g., may be sheath only,        and not sample or particles), at aligned position from step (2)        above.    -   b. System 200 aligns extinction x-axis to position for maximum        electromagnetic radiation transmission through microsorter flow        channels 203, by scanning nominal range, recording measured        optical power values, and averaging positions for all channels        203.        4) System 200 aligns chip 218 peak ratio.    -   a. System 200 flows sheath and sample to chip 218 (e.g., with        beads, cells, or other particles as a calibration particle).    -   b. System 200 calculates the desired peak ratio from the        geometry of chip 218 pinholes. For example, for a plurality of        pinholes, one could find a desired peak ratio (e.g., less than        1:1, or greater than 1:1).    -   c. System 200 aligns chip 218 x-axis for peak ratio by scanning        a nominal range, and for each channel 203 only use positions        where a good event rate or the like is above a pre-determined        threshold. System 200 then finds which valid position is closest        to a target peak ratio.    -   d. System 200 aligns chip 218 about the theta axis for peak        ratio by scanning a nominal range, and for each channel 203 only        use positions where a good event rate (i.e., events that are        considered acceptable with respect to defined event acceptance        attributes such as signal strength, threshold crossings, etc.)        or the like is above a pre-determined threshold. Then performs a        line fit of valid positions.    -   e. If slope of the line fit is above a threshold, system 200        uses the sign of the slope to determine which direction to move        theta axis, to reduce the line slope. System 200 then performs        another scan and re-calculates.    -   f. If slope of line fit is below a threshold, the theta peak        ratio alignment of chip 218 is complete.        5) System 200 aligns side scatter ribbon in x-axis.    -   a. System 200 flows sheath and sample through chip 218 with        beads, cells, or other particles.    -   b. System 200 aligns the side scatter ribbon 233 x-axis to        position for most electromagnetic radiation, by scanning nominal        range, recording measured side scatter values, and averaging        positions for all channels.        6) System 200 aligns fluorescence ribbon 235 in the x, y, z        axes.    -   a. System 200 flows sheath and sample through chip 218 with        beads, cells, or other particles.    -   b. System 200 aligns fluorescent ribbon 233 x-axis to position        for most electromagnetic radiation, by scanning nominal range,        recording measured fluorescent values, and averaging positions        for all channels.    -   c. Aligns fluorescent ribbon 233 y-axis to position for most        electromagnetic radiation, by scanning nominal range, recording        measured fluorescent values, and averaging positions for all        channels.    -   d. Aligns fluorescent ribbon 233 z-axis to position for most        electromagnetic radiation, by scanning nominal range, recording        measure fluorescent electromagnetic radiation values, and        averaging positions for all channels.

It is to be understood that for any of the alignment methods describedabove, one or more of the steps and/or sub-steps delineated above may beeliminated, that the steps and/or sub-steps need not necessarily beperformed in the order presented above, that one or more step, sub-stepsand/or blocks of steps and/or sub-steps may be repeated; and/oradditional and/or other steps and/or sub-steps may be interposed.

Exemplary Microfluidic Assembly/Chip 218 Alignment Methods:

In exemplary embodiments, system 200 may be configured and adapted toautomatically align (e.g., via sensors 216 and processor 214) thepinhole array on chip or chips 218 of system 200 with the optical pathbetween the segmented mirror (or other beam shaping optics) 225 and anoptical detector subsystem (e.g., the optical extinction detectorsubsystem 231) to ensure that the maximum electromagnetic radiation istransmitted through chip 218 substantially unobstructed. The opticaldetector subsystem may function as an optical power detector array.

It is noted that each newly inserted chip 218 into the chip-holder orthe like of system 200 may create micro-displacement of several (orseveral tens) of microns in any of multiple axes (x, y, z, yaw (theta),pitch, roll). As such, micron precision requirements of chip 218 orsystem 200 may warrant chip 218 to undergo an alignment procedure. Ingeneral, a chip-holder stage and/or a receptacle of system 200 may haveone motorized stage per axis to enable software controlled automatedalignment of chip 218.

In general, machine vision systems may use optical sensors or the like(e.g., point-wise scanning sensors that sense one sample at a time,one-dimensional array sensors that sense one line at a time,two-dimensional sensor arrays that sense an entire two-dimensional sceneat a time). In exemplary embodiments, system 200 of the presentdisclosure may utilize a hybrid of point-wise scanning sensors andone-dimensional array sensors due, in part, to the need for high spatialresolution and other hardware design considerations. In certainembodiments, the area of interest on a chip 218 or the like may beroughly about 70 mm by about 4 mm.

In exemplary embodiments, chip 218 alignment of system 200 is a processof proactively moving (automatically) the chip 218 in stages orincrements so that particular detection locations 222 a (e.g., anoperational row of pinholes) on a chip 218 may be properly positionedwith respect to the optical transmission of the electromagneticradiation (e.g., laser light) 227 to the detector assembly 226. This mayinvolve optical transmission of the electromagnetic radiation 227 fromthe segmented mirrors (or other beam shaping optics) 225 to sensorsand/or individual detectors on a fiber ribbon of an optical extinctionsubassembly 231.

In certain embodiments, it is noted that chips 218 used by system 200may be disposable, so several new chips 218 may be required to beinserted into system 200 each day. Moreover, due to imprecisions or thelike of some chip-holders/insertion methods, each inserted chip 218 maygenerally need to be aligned after insertion. It is also noted that, ingeneral, a manual chip 218 alignment process may be a tedious,time-consuming, subjective and/or unreliable process.

In exemplary embodiments, the automatic (i.e., operatorless) alignmentsystems and methods of system 200 may be highly repeatable, with thealignment results (optical transmission) not varying significantly fromone alignment repetition to another. In general, the automatic alignmentsystems and methods of chips 218 may be highly accurate, with thealignment position generally within about 5 microns of the desiredposition. Optionally, if such tight alignment tolerances are notrequired, the alignments may be accurate to within 10, to within 20 oreven within 30 microns. Moreover, the automatic alignment systems andmethods of chip 218 may be fully automated to self-navigate in the x, y,and theta (and other) axes spaces. Furthermore, the automatic alignmentsystems and methods of chips 218 of system 200 may be accomplished in ashort amount of time (e.g., in less than about 5 minutes, in less thanabout 30 seconds, in less than about 5 seconds, or in less than about 1second). As a non-limiting example, if higher accuracy is desired, thescanning increment may be approximately 5 microns and the time foralignment may be on the order of minutes. As another non-limitingexample, if a more nominal accuracy is sufficient, the scanningincrement may be approximately 30 microns and the time for alignment maybe on the order of minutes. In exemplary embodiments and as shown inFIG. 10, microfluidic chip 218 may include at least one fiducial marker.A fiducial is a reference point; a fiducial marker is an object placedin the field of view of an imaging system which appears in the imageproduced, for use as a point of reference or a measure. According to anaspect, chip 218 may include at least one Y-fiducial marker 255 and atleast one X-fiducial marker 257. The X- and Y-fiducial markers may beelongated marks oriented perpendicular (or at another angle) to oneanother. For example, a Y-fiducial marker may have a detectable featureextending in an x-direction (i.e., in a direction substantially parallelto a microfluidic channel 203 on chip 218) and an X-fiducial marker mayhave a detectable feature extending in a y-direction (i.e., in adirection substantially perpendicular to a microfluidic channel 203 onchip 218). In certain embodiments, chip 218 includes a first Y-fiducialmarker 255 and a first X-fiducial marker 257 proximal to a first end 261of chip 218, and a second Y-fiducial marker 255′ and a second X-fiducialmarker 257′ proximal to a second end 263 of chip 218. It is noted thatchip 218 may include any number of Y-fiducial markers 255 and/orX-fiducial markers 257. Moreover, chip 218 may include only Y-fiducialmarkers 255 or only X-fiducial markers 257. In general, the fiducialmarks may be any shape, number and/or orientation. Further, in general,the fiducial marks may include extinction, reflective, refractive,diffractive and/or even fluorescent elements, and thus, anyexcitation/detection system may be used to perform the operatorless chipalignment process. In a preferred aspect, the operatorless chipalignment process may use the same electromagnetic radiation 227 slatedto-be-used to interrogate a sample flowing through the microfluidicchannels 203 of the chip 218 and the optical extinction subassembly 231.In such instance, the fiducial elements may be extinction elementsformed on a transmissive substrate, may be mask elements formed on atransmissive substrate, may be apertures formed on a non-transmissivesubstrate, etc.

In exemplary embodiments, system 200 may be configured and adapted toautomatically align (e.g., via sensors 216 and processor 214) a pinholearray 229 on chip 218 with the optical path between the segmented mirror(and beam shaping optics) 225 and the optical power detector array 231to ensure that the maximum electromagnetic radiation is passing throughchip 218 substantially unobstructed. In certain embodiments and asdiscussed below, such automatic alignment may be accomplished byutilizing the Y-fiducial markers 255 and/or the X-fiducial markers 257or substantially only fiducial marker 255 and/or 257. In otherembodiments and also as discussed below, such automatic alignment may beaccomplished via a combination of fiducial marker 255 and/or 257navigation along with navigation utilizing other artifacts/markers onchip 218.

For example, in one embodiment the fiducial markers 255, 257 may belocated by system 200 and, based in part on known chip 218 topology orthe like, system 200 may then calculate (or otherwise determine) thecoordinates of the operational pinholes of chip 218. In exemplaryembodiments, such operatorless adjustment may be achieved by: (i) acoarse-to-fine approach, (ii) the calculation of theta rather thanscanning for various theta angles (theta axis), and/or (iii) sub-samplespatial resolution achieved based on a Gaussian fit.

In a further exemplary embodiment and as shown in FIGS. 11A-16B, system200 may be programmed, configured and adapted to automatically alignchip 218 by utilizing the following steps:

-   -   (i) coarsely scan chip 218 in the y-direction for Y-fiducial        markers 255 and/or 255′ (refer to arrows in FIG. 11A);    -   (ii) determine the coarse position of the Y-axis (Y_(coarse))        for chip 218, i.e., the position of the Y-axis that provides the        greatest intensity;    -   (iii) coarsely scan chip 218 in the x-direction for X-fiducial        markers 257 and/or 257′ (refer to arrows in FIG. 12A);    -   (iv) determine the slant angle Theta_(coarse) for chip 218        (refer to FIG. 13A);    -   (v) deslant chip 218 by −Theta_(coarse) (refer to FIG. 13B);    -   (vi) re-scan chip 218 finely in the x-direction to get to the        fine X_(align) position (refer to FIG. 14A);    -   (vii) determine fine slant angle Theta_(align) (refer to FIG.        14B);    -   (viii) deslant by −Theta_(align);    -   (ix) fine scan in the y-direction around Y_(coarse) and find        fine Y_(align) position (refer to FIGS. 15A and 15B);    -   (x) move to the X_(align), X_(align) position for chip 218; and    -   (xi) acquire signal (e.g., electromagnetic radiation passing        through chip 218) (refer to FIG. 16B).

FIGS. 11A and 11B illustrate a coarse scanning process wherein: (i) themicrofluidic chip 218 is moved in the y-direction using a motor-drivenstage to detect the Y-fiducials (FIG. 11A); and (ii) data is collectedand plotted for each increment of the coarse scanning process (FIG.11B). In the first three-dimensional graph, data is presented as signalintensity for each microfluidic channel and for each y-directionscanning increment or position. In this particular graph, theincremental scanning step in the y-direction is 100 microns. In thetwo-dimensional graph, the peak signal intensity is plotted with respectto each microfluidic channel and its scanned position.

FIGS. 12A and 12B illustrate a coarse scanning process wherein: (i) themicrofluidic chip 218 is moved in the x-direction to detect theX-fiducials (FIG. 12A); and (ii) data is collected and plotted for eachincrement of the coarse scanning process (FIG. 12B). In thethree-dimensional graph, data is presented as signal intensity for eachmicrofluidic channel and for each x-direction scanning increment orposition. In this particular graph, the incremental scanning step in thex-direction is 100 microns.

FIGS. 13A and 13B illustrates that a coarse slant angle may bedetermined from data generated from the coarse scanning steps of FIG.12A. In the three-dimensional graph of FIG. 13A, data is presented assignal intensity for each microfluidic channel and for each x-directionscanning increment or position. In this particular graph, theincremental scanning step in the x-direction is 100 microns. In thetwo-dimensional graph of FIG. 13B, the peak signal intensity of the twofiducial markers 257, 257′ are plotted across the channels. If the chip218 was perfectly aligned, the difference between the scan increment forthe first X-fiducial 257 would be the same as the scan increment for thesecond X-fiducial 257′. The difference between the scan increment valuefor the first X-fiducial and the second X-fiducial and the knowndistance between the fiducials is used to calculate a theta_(coarse)value. The chip 218 may then be rotated by an amount equal to thenegative of the theta_(coarse) value to obtain a coarsely alignedangular position.

FIGS. 14A and 14B illustrate a fine scanning process wherein: (i) themicrofluidic chip 218 is moved in the x-direction to detect theX-fiducials (FIG. 14A); and (ii) data is collected, plotted and analyzedto determine a fine X_(align) value and a fine theta_(align) value basedon this fine scanning process (FIG. 14B). In the three-dimensionalgraph, data is presented as signal intensity for each microfluidicchannel and for each x-direction scanning increment or position. In thisparticular graph, the incremental scanning step in the x-direction is 10microns. In the lower two-dimensional graph, the peak signal intensityof the two fiducial markers 257, 257′ are plotted across the channels.The difference in the scan increment value for the first and secondX-fiducial and the known distance between the fiducials is used tocalculate a theta_(align) value. The chip 218 may then be rotated by anamount equal to the negative of the theta_(coarse) value to obtain afinely aligned angular position.

FIGS. 15A and 15B illustrate a fine scanning process wherein: (i) themicrofluidic chip 218 is moved in the y-direction to detect theY-fiducials (FIG. 15A); and (ii) data is collected, plotted and analyzedto determine a fine Y_(align) positioning value (FIG. 15B).

FIG. 16A illustrates the microfluidic chip 218 moved through its fineX_(align) and Y_(align) positioning values to its final alignedposition. Each microfluidic channel is thus automatically properlyaligned with the electromagnetic radiation source so that particleprocessing data may be acquired. Data may be acquired to verify thealignment (FIG. 16B).

During the scanning operations, microfluidic chip 218 may be motordriven in the x- or y-directions. Extinction data may be collectedduring each step. A typical coarse scan step dimension may range from 50microns to 300 microns. Preferably, the coarse scan step dimension maybe less than approximately 150 microns. As an example, the coarse scanstep dimension associated with FIGS. 11A and 12A may be 100 microns. Atypical fine scan step dimension may range from 5 microns to 50 microns.Preferably, the fine scan step dimension may be less than approximately20 microns. As an example, the fine scan step dimension associated withFIGS. 14A and 15A may be 10 microns. In general, the coarse scanincrement may be from 5 times to 20 times the fine scan increment. In apreferred embodiment, the coarse scan increment may be approximately 10times the fine scan increment. The scan increments (coarse and/or fine)in the x-direction need not be the same as the scan increments (coarseand/or fine) in the y-direction. Theta is calculated based on knowndimensions associated with the fiducials and the measured relativepositions of the fiducial signals. During the deslant operations,microfluidic chip 218 may be motor driven around the z-axis.

In general, the X-fiducial(s) and the Y-fiducial(s) may be any length,orientation and/or shape. Typically, the X- and Y-fiducial(s) may belocated outside of the pinhole array 229 and/or the signal collectionregion utilized during particle processing runs.

According to certain embodiments, only a single Y-fiducial may beprovided. In such case, the microfluidic chip 218 may be scanned in they-direction for the Y-fiducial, the chip 218 may be translated in thex-direction, and then chip 218 may be rescanned in the y-direction forthe Y-fiducial at the second x-direction station. Thus theta may bedetermined based on a single Y-fiducial.

According to some embodiments, only a single X-fiducial may be provided.In such case, the microfluidic chip 218 may be scanned in thex-direction for the X-fiducial, the chip 218 may be translated in they-direction, and then chip 218 may be rescanned in the x-direction forthe X-fiducial at the second y-direction station. Thus theta may bedetermined based on a single X-fiducial.

According to some embodiments, theta may be determined based on theY-fiducial(s) alone. The one or more X-fiducials may be used to locatethe chip 218 in the x-direction. Alternatively, theta may be determinedbased on the X-fiducial(s) alone. The one or more Y-fiducials may beused to locate the chip 218 in the y-direction.

According to other embodiments, the coarse scan in the x-direction forthe X-fiducials step (iii) may be eliminated from the alignmentprocedure.

According to even other embodiments, only coarse scans may be performedand the deslant operation may be based on the coarse scan data.Alternatively, only fine scans may be performed and the deslantoperation may be based on the fine scan data. As even anotheralternative, only coarse scans in the x-direction may be performed andonly fine scans in the y-direction may be performed (or vice versa).

In even another embodiment and as shown in FIGS. 17A-24B, a subset ofthe fiducial markers (e.g., Y-fiducial markers 255, 255, when theX-fiducial markers 257, 257 are obscured) may be located by system 200and other artifacts/markers (pinhole rows, channels 203, actuationpoints, etc.) on chip 218 may be identified to navigate to and/orcalculate the coordinates of the operational pinholes of chip 218.

More specifically and as shown in FIGS. 17A-24B, system 200 may beconfigured and adapted to automatically align chip 218 by utilizing thefollowing steps:

-   -   (i) coarsely scan chip 218 in the y-direction for Y-fiducial        markers 255 and/or 255′ (refer to arrows in FIG. 17A);    -   (ii) find coarse Y position value (Y_(coarse)) for chip 218;    -   (iii) coarsely scan chip 218 in the x-direction for pinholes        (X_(coarse)) (refer to arrows in FIG. 18A);    -   (iv) determine a fine slant Theta_(align) for chip 218 based on        the coarse scanning of the pinholes (e.g., using Radon Transform        with sub-degree precision or other suitable mathematical        algorithms);    -   (v) deslant chip 218 by the negative of the fine slant angle        −Theta_(align) (refer to deslanted chip 218 of FIG. 19A);    -   (vi) re-scan chip 218 coarsely in the x-direction and determine        the middle pinhole row X_(coarse) (e.g., using an        autocorrelation function on the integral of the optical        transmission to find a pitch and then finding the second peak)        (refer to FIGS. 19B and 20);    -   (vii) fine scan in the x-direction around X_(coarse), (refer to        FIG. 21A) and then find X_(align) (using, for example, a        Gaussian fit) (refer to FIGS. 22A and 22B);    -   (viii) fine scan in the y-direction around X_(coarse), and find        Y_(align) (using, for example, a Gaussian fit) (refer to FIG.        23A);    -   (ix) move to the X_(align) and Y_(position) for chip 218; and    -   (x) acquire signal (e.g., electromagnetic radiation passing        through chip 218) (refer to FIG. 24B).

FIGS. 17A and 17B illustrate a coarse scanning process wherein: (i) themicrofluidic chip 218 is moved in the y-direction using a motor-drivenstage to detect the Y-fiducials (FIG. 17A); and (ii) data is collectedand plotted for each increment of the coarse scanning process (FIG.17B). In the upper graph, data is three-dimensionally presented with arelative signal intensity being plotted for each microfluidic channeland for each y-direction scanning increment or position. In thisexemplary graph, the incremental scanning step in the y-direction is 100microns. In the lower graph, the peak signal intensity is plotted withrespect to each microfluidic channel and its scanned position.

FIGS. 18A and 18B illustrate a coarse scanning process wherein: (i) themicrofluidic chip 218 is moved in the x-direction to detect the pinholesassociated with each microfluidic channel (FIG. 18A); and (ii) data iscollected and plotted for each increment of the coarse scanning process(FIG. 18B). In the three-dimensional graph, data is presented asrelative signal intensity for each microfluidic channel and for eachx-direction scanning increment or position. In this upper graph, theincremental scanning step in the x-direction is 100 microns. In thelower graph, the peak signal intensity for each pinhole is plotted withrespect to each microfluidic channel and its scanned position.

In FIG. 19A the microfluidic chip 218 has been deslanted by the negativeof a slant angle theta_(align) determined from data generated from thecoarse scanning steps using a mathematical algorithm such as a RadonTransform. The deslanted chip 218 is coarsely scanned in the y-directionand signal intensity associated with each pinhole is measured (FIG.19A). In the graph of FIG. 19B, a relative signal intensity for eachpinhole 229 is plotted for each microfluidic channel and for eachy-direction scanning increment or position.

Referring to FIG. 20, the optical transmissions of the pinholes for thedata collected in FIG. 19B are graphed as a function of scan incrementand the location of the middle pinhole row is determined. This providesa coarse X position (X_(coarse)). The location of the middle pinhole row229 b may be determined using an autocorrelation function on theintegral of the optical transmission to find a pitch and then findingthe second peak.

FIGS. 21A and 21B illustrate a fine scanning process wherein: (i) themicrofluidic chip 218 is moved in the x-direction to detect a signalemanating from the second pinholes (FIG. 21A); and (ii) data iscollected, plotted and analyzed to determine a fine X position value(X_(align)) (FIG. 21B). In the three-dimensional graph, data ispresented as signal intensity for each of the middle pinholes associatedwith a microfluidic channel and for each x-direction scanning incrementor position. In this graph, the incremental scanning step in thex-direction is 10 microns. In the lower two-dimensional graph, the peaksignal intensity and the signal intensity spread for each second pinholeare plotted for each of the microfluidic channels.

Generally, an excitation source has a Gaussian profile. It may bedesirable to find the edge of the profile and/or the peak value. Asshown in FIGS. 22A and 22B, a Gaussian fit of the pinhole intensitysignal may be used to determined peak and edge values for each pinhole.FIG. 22A shows the optical power data for the second pinhole for thefirst microfluidic channel. FIG. 22B shows the optical power data forthe second pinhole for the fourth microfluidic channel.

FIGS. 23A and 23B illustrate a fine scanning process wherein: (i) themicrofluidic chip 218 is moved in the y-direction to detect a signalemanating from the second pinholes (FIG. 23A); and (ii) data iscollected, plotted and analyzed to determine a fine Y position value(Y_(align)) (FIG. 23B). In the three-dimensional graph, data ispresented as signal intensity for each of the middle pinholes associatedwith a microfluidic channel and for each y-direction scanning incrementor position. In this graph, the incremental scanning step in they-direction is 10 microns. In the lower two-dimensional graph, the peaksignal intensity and the signal intensity spread for each second pinholeare plotted for each of the microfluidic channels. Again, a Gaussian fitof the pinhole intensity signal may be used to determined peak and edgevalues for each pinhole.

FIG. 24A illustrates that the microfluidic chip 218 is moved through itsfine X_(align) and Y_(align) positioning values to its final alignedposition. Each microfluidic channel is thus automatically properlyaligned with the electromagnetic radiation source so that particleprocessing data may be acquired. Data may be acquired to verify thealignment (FIG. 24B).

According to certain embodiments, all fine scanning steps may use aGaussian fit to determine the fine X_(align) and/or Y_(align) positionvalues. As a non-limiting example, the fine scan increment may be 10microns and the Gaussian fit may be of subset precision.

It is to be understood that for any of the processes described above,one or more of the steps and/or sub-steps delineated above may beeliminated, that the steps and/or sub-steps need not necessarily beperformed in the order presented above, that one or more step, sub-stepsand/or blocks of steps and/or sub-steps may be repeated; and/oradditional and/or other steps and/or sub-steps may be interposed.

Although the systems, assemblies and methods of the present disclosurehave been described with reference to exemplary embodiments thereof, thepresent disclosure is not limited to such exemplary embodiments and/orimplementations. For example, certain aspects that have been describedwith respect to system 100 may be equally applicable to system 200 (andvice versa). Indeed, the systems, assemblies and methods of the presentdisclosure are susceptible to many implementations and applications, aswill be readily apparent to persons skilled in the art from thedisclosure hereof. The present disclosure expressly encompasses suchmodifications, enhancements and/or variations of the disclosedembodiments. Since many changes could be made in the above constructionand many widely different embodiments of this disclosure could be madewithout departing from the scope thereof, it is intended that all mattercontained in the drawings and specification shall be interpreted asillustrative and not in a limiting sense. Additional modifications,changes, and substitutions are intended in the foregoing disclosure.Accordingly, it is appropriate that the appended claims be construedbroadly and in a manner consistent with the scope of the disclosure.

What is claimed is:
 1. A method for automatically aligning amicrofluidic chip for a particle processing system, the methodcomprising: receiving a microfluidic chip into a chip receptacle;illuminating the microfluidic chip with a radiation source; detectingextinction signals; coarsely scanning the chip in a first-direction, asecond-direction, or both the first and second-direction to generateextinction signals; determining a coarse slant angle based on adimension determined from the coarse scanning and a known dimension ofthe microfluidic chip; rotating the microfluidic chip by the negative ofthe coarse slant angle; finely scanning the chip in a first-direction, asecond-direction, or both the first- and second-direction to generateextinction signals; determining a fine slant angle based on a dimensiondetermined from the fine scanning and a known dimension of themicrofluidic chip; and rotating the microfluidic chip by the negative ofthe fine slant angle.
 2. The method of claim 1, wherein the microfluidicchip is removably received into the chip receptacle.
 3. The method ofclaim 1, wherein the microfluidic chip includes a pair of separatedfiducials and the step of coarsely scanning includes scanning at leastone of the fiducials.
 4. The method of claim 1, wherein a coarsescanning step increment ranges from approximately 50 microns to 200microns.
 5. The method of claim 1, wherein a fine scanning stepincrement ranges from approximately 5 microns to 50 microns.
 6. Themethod of claim 1, wherein the step of coarsely scanning includes movingthe microfluidic chip relative to a radiation source.
 7. The method ofclaim 1, wherein the step of coarsely scanning includes scanning themicrofluidic chip across a plurality of microfluidic channels.
 8. Themethod of claim 1, wherein the microfluidic chip includes a plurality ofpinholes associated one or more microfluidic channels and the step ofcoarsely scanning includes scanning the pinholes associated with the oneor more microfluidic channels.
 9. The method of claim 1, furthercomprising: determining a first-direction coarse misalignment distancebased on the coarse scanning; and translating the microfluidic chip bythe negative of the first-direction coarse misalignment position. 10.The method of claim 9, further comprising: determining a first-directionfine misalignment distance based on the fine scanning; and translatingthe microfluidic chip by the negative of the first-direction finemisalignment position.